Personal athlete monitoring system

ABSTRACT

An athlete monitoring system includes body position beacons, a localized radar system, a foot force detection system, and a processing module. The beacons are positioned at various locations on the body of the athlete. The localized radar system creates a localized radar coordinate system in which the athlete is positioned and, at a first sampling rate, produces frames of body position data based on determining location of the beacons within the localized radar coordinate system. The foot force detection system generates frames of left foot force data and frames of right foot force data. The processing module correlates the frames of body position data, the frames of left foot force data, and the frames of right foot force data to produce integrated ground-body interaction data and athletic movement data.

CROSS-REFERENCE TO RELATED APPLICATIONS

The present U.S. Utility patent application claims priority pursuant to35 USC § 120 as a continuation-in-part of U.S. Utility application Ser.No. 15/679,831 entitled, “WIRELESS IN-SHOE PHYSICAL ACTIVITY MONITORINGAPPARATUS”, filed Aug. 17, 2017, which claims priority pursuant to 35U.S.C. § 119(e) to U.S. Provisional Application No. 62/376,555, entitled“IN-SHOE GROUND REACTIVE FORCE MEASURING SYSTEM”, filed Aug. 18, 2016,all of which are hereby incorporated herein by reference in theirentirety and made part of the present U.S. Utility patent applicationfor all purposes.

The present U.S. Utility patent application also claims prioritypursuant to 35 U.S.C. § 120 as a continuation-in-part of co-pending U.S.Utility patent application Ser. No. 17/575,594, entitled “INSOLE XYZFORCE DETECTION SYSTEM,” filed Jan. 13, 2022, which claims prioritypursuant to 35 U.S.C. § 119(e) to U.S. Provisional Application No.63/202,251, entitled “INSOLE XYZ FORCE DETECTION SYSTEM,” filed Jun. 3,2021, both of which are hereby incorporated herein by reference in theirentirety and made part of the present U.S. Utility patent applicationfor all purposes.

STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT

Not Applicable.

INCORPORATION-BY-REFERENCE OF MATERIAL SUBMITTED ON A COMPACT DISC

Not Applicable.

BACKGROUND OF THE INVENTION Technical Field of the Invention

This disclosure relates generally to athletic data gathering andanalysis and more particularly to force data.

Description of Related Art

Technology is being used more and more to monitor a person's physicalactivities, rest patterns, diet, and vital signs. Some of thistechnology is wearable. For example, there are wrist wearable devices tomonitor the number of steps a person takes in a day, the approximatedistance traveled, heart rate, and/or sleep patterns. As anotherexample, there are chest straps that communicate wirelessly with amodule for monitoring heart rate.

As yet another example, there are shoe insert systems to monitor forcesof the foot during walking. One such system includes a flexible circuitboard insert that includes a resistive sensor grid that is hard wired toa module that straps to the ankle. The two ankle modules are then hardwired to another module that straps to the waist. The waist modulecollects the data and communicates it to a computer via a wired orwireless connection.

Another technology for monitoring foot force is to use a pressuresensitive mat on which a person stands to perform a physical activity(e.g., golf). The mat detects variations in foot forces during theexecution of the physical activity, which is then analyzed to evaluatethe performance of the physical activity.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWING(S)

The patent or application file contains at least one drawing executed incolor. Copies of this patent or patent application publication withcolor drawing(s) will be provided by the Office upon request and paymentof the necessary fee.

FIG. 1A is a top side view diagram of an embodiment of shoes thatinclude a force detection system;

FIG. 1B is a medial side view diagram of an embodiment of a shoe of FIG.1A;

FIG. 2 is a schematic block diagram of a cross-section an embodiment ofa shoe including a force detection system;

FIG. 3 is a schematic block diagram of an embodiment of force detectionsystem that is capable of communicating with a computing device;

FIG. 4A is a schematic block diagram of an embodiment of a drive sensecircuit coupled to a variable capacitor and to an ADC;

FIG. 4B is a schematic block diagram of an example of a referencesignal;

FIGS. 5A-5D are schematic block diagrams of embodiments of computingdevices;

FIGS. 5E-5I are schematic block diagrams of embodiments of computingentities;

FIGS. 6A-6C are schematic block diagrams of an embodiment of forcedetection system that includes a layer of variable capacitors, a layerof compression plates, and a circuitry section;

FIGS. 6D-6F are schematic block diagrams of another embodiment of forcedetection system that includes a layer of variable capacitors, a layerof compression plates, and a circuitry section;

FIGS. 7A-7C are schematic block diagrams of an embodiment of forcedetection system that includes a layer of variable capacitors and acircuitry section;

FIGS. 8A-8C are schematic block diagrams of an example of force appliedby a foot to the force detection system;

FIGS. 9A-9C are schematic block diagrams of another example of forceapplied by a foot to the force detection system;

FIGS. 10A-10C are schematic block diagrams of another example of forceapplied by a foot to the force detection system;

FIGS. 11A-11F are schematic block diagrams of another example of forcesapplied by a foot to the force detection system when a person isrunning;

FIG. 12 is a schematic block diagram of another embodiment of a layer ofvariable capacitors and a layer of compression plates of a forcedetection system;

FIG. 13 is a schematic block diagram of another embodiment of a layer ofvariable capacitors FIG. 12 without a layer of compression plates of aforce detection system;

FIGS. 14A-14C are schematic block diagrams of an example of a layer ofvariable capacitors and a layer of compression plates of a forcedetection system;

FIGS. 15A-15E are schematic block diagrams of an example of a layer ofvariable capacitors and a layer of compression plates of a forcedetection system with and without compression of the capacitors;

FIGS. 16A-16C are schematic block diagrams of examples of a geometricand electrical relationship between variable capacitors of a secondlayer and a compression plate of a first layer within a force detectionsystem;

FIG. 17 is a schematic block diagram of an example of a graph thatdepicts capacitance variance with respect to compression of a ofvariable capacitor;

FIGS. 18A-18C are schematic block diagrams of examples of an impactforce applied to a cell of a force detection system, wherein the cellincludes a compression plate and three or more variable capacitors;

FIGS. 18D-18F are schematic block diagrams of examples of an impactforce applied to a cell of a force detection system (e.g., a first layercapacitor and three second layer capacitors);

FIGS. 19A-19B are schematic block diagrams of an example of determininga normal vector of a reference plane of a cell of a force detectionsystem in response to an impact force;

FIGS. 20A-20D are schematic block diagrams of another example ofdetermining a normal vector of a reference plane of a cell of a forcedetection system in response to an impact force;

FIGS. 21A-21D are schematic block diagrams of another example ofdetermining a normal vector of a reference plane of a cell of a forcedetection system in response to an impact force;

FIGS. 22A-22C are schematic block diagrams of an example of determininga plurality of normal vectors of a plurality of reference planes of aplurality of cells of a force detection system in response to an impactforce;

FIG. 23 is a schematic block diagram of an example of two cells, eachhaving a top layer capacitor (TC) (light green) and a four lower layercapacitors (green, blue, red, black);

FIGS. 24A-24B are schematic block diagrams of examples of impact forcesimpacting a cell of FIG. 23.

FIG. 25 is a schematic block diagram of an example of a plurality ofcells;

FIGS. 26A-26D are schematic block diagrams of an example of determiningone or more normal vectors in response to an impact force;

FIGS. 27A-27C are schematic block diagrams of an example of determininga normal vector of a cell of a force detection system in response to animpact force;

FIGS. 28A and 28B are schematic block diagrams of examples of placementof force cells within a sole of a shoe with respect to expected forcesapplied by a foot;

FIG. 29 is a schematic block diagram of an example of an angular impactforce applied by a foot on the force detection system;

FIG. 30 is a schematic block diagram of another example of an angularimpact force applied by a foot on the force detection system;

FIG. 31 is a schematic block diagram of another example of cellplacement in a sole with respect to expected forces applied by a foot;

FIGS. 32A-32C are schematic block diagrams of another embodiment offorce detection system that includes a layer of variable capacitors, alayer of compression plates, and a circuitry section;

FIGS. 33A-33E are schematic block diagrams of an example of a capacitorcell of the force detection system of FIGS. 32A-32C;

FIG. 34 is a logic diagram of an example of establishing a foot forcesampling rate;

FIG. 35 is a schematic block diagram of an example of a foot forcesampling rate;

FIG. 36 is a schematic block diagram of an example of a foot forcepattern;

FIG. 37 is a schematic block diagram of another example of a foot forcepattern;

FIG. 38 is a schematic block diagram of another example of a foot forcepattern;

FIG. 39 is a schematic block diagram of an embodiment of a foot forcedetection system;

FIG. 40 is a schematic block diagram of another embodiment of a footforce detection system;

FIG. 41 is a schematic block diagram of an example of processing footforce detection;

FIG. 42 is a schematic block diagram of another example of processingfoot force detection;

FIG. 43 is a schematic block diagram of another example of processingfoot force detection;

FIG. 44 is a graphic diagram of an example of signals of the example ofFIG. 43;

FIG. 45 is a schematic block diagram of another example of processingfoot force detection;

FIG. 46 is a graphic diagram of an example of signals of the example ofFIG. 45;

FIG. 47 is a schematic block diagram of an example of sampling periodfor foot force detection;

FIG. 48 is a schematic block diagram of another example of processingfoot force detection;

FIG. 49 is a schematic block diagram of an embodiment of an athletemonitoring system;

FIG. 50 is a schematic block diagram of an example of a local coordinatesystem of an athlete monitoring system;

FIG. 51 is a schematic block diagram of an example of athletemonitoring;

FIG. 52 is a schematic block diagram of an example of athlete relativepositioning;

FIG. 53 is a schematic block diagram of an example of athlete coordinatesystem positioning;

FIG. 54 is a schematic block diagram of an example of determiningathlete relative positioning;

FIG. 55 is a schematic block diagram of another example of determiningathlete relative positioning;

FIG. 56 is a schematic block diagram of another example of determiningathlete relative positioning;

FIG. 57 is a logic diagram of an example of method for determiningathlete positioning;

FIG. 58 is a schematic block diagram of another example of athletepositioning;

FIG. 59 is a schematic block diagram of an embodiment of an athletemonitoring system;

FIG. 60 is a schematic block diagram of another embodiment of foot forcedetection system;

FIG. 61 is a schematic block diagram of an embodiment of a power unit ofa foot force detection system;

FIG. 62 is a schematic block diagram of an example of a power harvestingcircuit of a power unit;

FIG. 63 is a schematic block diagram of another example of a powerharvesting circuit of a power unit;

FIG. 64 is a schematic block diagram of another example of a powerharvesting circuit of a power unit;

FIG. 65 is a schematic block diagram of another example of a powerharvesting circuit of a power unit;

FIGS. 66A-66D are side view diagrams of other embodiments of a pair ofshoes that each include a shoe sensor system;

FIG. 67 is a schematic block diagram of an embodiment of a wirelessin-shoe physical activity monitoring apparatus and a computing device;

FIG. 68 is a schematic block diagram of an example of communication viathe body;

FIG. 69 is a schematic block diagram of an example of communication viathe body;

FIG. 70 is a schematic block diagram of an embodiment of a shoe sensorsystem;

FIG. 71 is a logic diagram of an example of a method executed by aprocessing module;

FIGS. 72-75 are examples of timing and data diagrams of a shoe sensorsystem;

FIGS. 76A and 76B are top view diagrams of an example of positioningpressure sensing elements within a pair of shoes;

FIGS. 77A and 77B are top view diagrams of another example ofpositioning pressure sensing elements within a pair of shoes;

FIGS. 78A and 78B are top view diagrams of an example of the pressuresensing elements positioned with respect to an insole of a right shoeand the control circuit positioned with respect to a midsole of a rightshoe;

FIGS. 79A and 79B are top view diagrams of an example of the pressuresensing elements positioned with respect to an insole of a left shoe andthe control circuit positioned with respect to a midsole of a left shoe;

FIG. 80A is a top view diagram of another example of the control circuitand accelerometer positioned with respect to a midsole of a left shoe;

FIG. 80B is a top view diagram of another example of the control circuitand accelerometer positioned with respect to a midsole of a right shoe;

FIG. 81A is a top view diagram of another example of the control circuitand two accelerometers positioned with respect to a midsole of a leftshoe;

FIG. 81B is a top view diagram of another example of the control circuitand two accelerometers positioned with respect to a midsole of a rightshoe;

FIG. 82 is a side view diagram of another example of the pressuresensing elements positioned with respect to an insole of a shoe and thecontrol circuit and accelerometer positioned with respect to a midsoleof the shoe;

FIG. 83 is a front view diagram of another example of the pressuresensing elements positioned with respect to an insole of a shoe;

FIG. 84 is a rear-view diagram of another example of the pressuresensing elements positioned with respect to an insole of a shoe;

FIG. 85 is a side view diagram of another example of the pressuresensing elements positioned with respect to an insole of a shoe and thecontrol circuit and accelerometer positioned with respect to a midsoleof the shoe;

FIG. 86 is a logic diagram of an example of generating foot force data;

FIG. 87 is a logic diagram of another example of generating foot forcedata;

FIG. 88 is a schematic block diagram of another example of generatingfoot force data;

FIG. 89 is a schematic block diagram of another example of generatingfoot force data;

FIG. 90 is a schematic block diagram of another example of generatingfoot force data;

FIG. 91 is a front view diagram of another example of the pressuresensing elements positioned with respect to an insole of a shoe;

FIG. 92 is a front view diagram of another example of the pressuresensing elements positioned with respect to an insole of a shoe;

FIG. 93 is a schematic block diagram of another embodiment of a shoesensor system;

FIG. 94 is a schematic block diagram of another embodiment of a shoesensor system;

FIG. 95 is a schematic block diagram of another embodiment of a shoesensor system;

FIG. 96 is a top view diagram of an example of the pressure sensingelements and corresponding antennas positioned with respect to an insoleof a shoe;

FIG. 97 is a side view diagram of an example of the antennas positionedwith respect to an insole of a shoe and the control circuit, with anantenna, and accelerometer positioned with respect to a midsole of theshoe;

FIG. 98 is a top and a side view diagram of an example of the pressuresensing element antennas positioned with respect to the antenna of thecontrol circuit;

FIG. 99 is a top and a side view diagram of another example of thepressure sensing element antennas positioned with respect to the antennaof the control circuit;

FIG. 100 is a schematic block diagram of an embodiment of a pressuresensing element;

FIG. 101 is a schematic block diagram of another embodiment of apressure sensing element;

FIG. 102 is a schematic block diagram of another embodiment of apressure sensing element;

FIGS. 103A-103D are schematic block diagrams of example embodiments of apressure sensor;

FIG. 104 is a top view diagram of an example of the pressure sensingelements and corresponding NFC coils positioned with respect to aninsole of a shoe in accordance with the present invention;

FIG. 105A is a side view diagram of an example of receiving NFC coilspositioned with respect to an insole of a shoe and a transmitting NFCcoil positioned with respect to a midsole of the shoe;

FIG. 105B is a side view diagram of an example of receiving NFC coilspositioned with respect to an insole of a shoe and transmitting NFCcoils positioned with respect to a midsole of the shoe;

FIG. 106 is a logic diagram of another example of a method executed by ashoe sensor system;

FIG. 107 is a logic diagram of another example of a method executed by ashoe sensor system;

FIG. 108 is a logic diagram of another example of a method executed by ashoe sensor system;

FIG. 109 is a logic diagram of another example of a method executed by ashoe sensor system;

FIG. 110 is a logic diagram of another example of a method executed by ashoe sensor system;

FIG. 111 is a logic diagram of another example of a method executed by ashoe sensor system;

FIG. 112 is a logic diagram of another example of a method executed by ashoe sensor system;

FIG. 113 is a logic diagram of another example of a method executed by ashoe sensor system;

FIG. 114 is a logic diagram of another example of a method executed by ashoe sensor system;

FIG. 115 is a logic diagram of another example of a method executed by ashoe sensor system in accordance with the present invention; and

FIG. 116 is a logic diagram of another example of a method executed by ashoe sensor system in accordance with the present invention.

DETAILED DESCRIPTION OF THE INVENTION

FIG. 1A is a top side view diagram of an embodiment of shoes 10 thatinclude a force detection system 20. Each shoe includes an upper section14, a vamp section 16, a quarter section 15, a securing mechanism 17,and at least a portion of the force detection system 20. For example,the left shoe includes a left shoe portion of the force detection system20-L and the right shoe includes a right shoe portion of the forcedetection system 20-R.

The upper section 14 includes the vamp section 16, which covers at leasta portion of a midfoot area of the shoe, and the quarter section 15,which is the rear portion of the shoe. The vamp section and the quartersection may be constructed from one or more the same materials or one ormore of different materials. The materials include, but is not limitedto, a leather, a molded plastic, a molded carbon fiber, a polyurethane(PU), a thermoplastic polyurethane (TPU), a faux leather, a PU leather,cloth, etc. In a specific example, the vamp section and the quartersection are constructed of leather. In another specific example, thevamp section is constructed for leather and the quarter section isconstructed of a PU leather.

The securing mechanism 17 functions to tighten the shoe 10 around a footwhen placed in the shoe 10. The securing mechanism 17 may be implementedin a variety of ways and positioned within the vamp section 16 is avariety of locations. For example, the securing mechanism 17 includeseyelets and a shoelace that is positioned approximately along a centerline of the vamp section 16. With respect to FIG. 1A, the center line isapproximately along a midline between a medial edge of the shoe and alateral edge of the shoe running the length of the vamp section 16. Inanother example, the securing mechanism 17 includes Velcro™ straps. Inanother embodiment, the securing mechanism 17 includes a Boa™ structure.

The force detection system 20 is included in one or both shoes. Ingeneral, the force detection system 20 provides X, Y, and/or Z forcedata of a foot within the shoe with respect to the ground. The forcedata can be used to evaluate human movement, which includes athleticmovement. For a body to move, it applies a force on the ground and theground pushes back with an equal and opposite force. The ground pushingback is called ground reaction force, which traverses through the shoes.

The direction and magnitude of ground reaction force effect humanmovement, especially athletic movements. Performance of almost everyathletic movement is improved by increasing power and/or increasingconsistency. Power is a function of energy divided by time. Energy is afunction of force excreted over a distance. Thus, power is a function offorce exerted over a distance in a given time frame. As such, power isincreased by increasing the force, increasing the distance, and/orreducing the time frame.

For an athletic movement, the force is ground reaction force. As such,an athlete's power is a function of the ground reaction force being usedto move the body, and may further includes moving an object (e.g., aclub, a bat, a ball, a racket, etc.), over a distance in a given timeframe. Thus, improving ground reaction force for the same distance andtime of movement, improves an athlete's power. Accordingly, determiningthe magnitude of ground reaction force during an athletic movement is animportant data point for improving athletic performance.

In athletics, consistency involves being able to move the body in anearly identical matter time after time. The direction of the groundreaction force effects an athlete's consistency. Ideally, an athletewants the direction of the ground reaction force to be parallel to theline of the legs. In the ideal case, there is no wasted force, all of itis going into the body. It also keeps the body in the properly alignmentfor the athletic movement (e.g., a golf swing).

The more the direction of the ground reaction force deviates fromparallel to the leg, the more of it is wasted and the more the athletehas to compensate for the deviation. Having to compensate for groundreaction force's angle deviation adds an extra element to the athleticmovement, which too must be executed nearly identical time after time toachieve the desired athletic consistency. Thus, determining thedirection of ground reaction force during an athletic movement is animportant data point for improving athletic performance.

Commercially available foot force systems suffer from one or more of thefollowing. (a) Due to the bulk of the system, it cannot be used in gameor in practice. It has to be used in a lab setting. (b) The forcesensors break down too quickly for elite athletes. When an athletejumps, they can have a landing impact of six times their body weight.For a professional football player that weighs over three hundredpounds, that is a landing force per jump of almost one ton. Most sensorsare design for a walking impact of about two times the body weight,hence they fail quickly when used by elite athletes. (c) The batteriesof a system need to be recharged too frequently. Most athletes,especially at the elite level, will not recharge the batteries on aregular basis (e.g., daily, every other day, multiple times per day,etc.). (d) The system only provides Z force information; there is noangular information, only magnitude information in the Z direction. (e)The system has a low sampling rate (e.g., a few hundred Hertz), thushigh-speed data is often missed or incomplete. For example, the footstrike of a sprinter happens in 10's of milliseconds; with a 200 Hertzsampling rate, that is one sample per 5 milliseconds, thus, very fewsamples will be captured for each foot strike, which will miss thegranularity and force transition of a foot strike.

The force detection system 20 is a force system that can be used in gameand/or in practice. A capacitor-based sensor array allows for hundredsto thousands of hours of reliable use. The force detection system isultra-low power such that the batteries can be charged infrequently. Theforce detection system provides X, Y, and Z force data such thatdirection and magnitude of ground reaction force can be determined andevaluating with respect to athletic performance. The force detectionsystem is capable of sampling data in the thousands to tens of thousandsof Hertz so a significant number of data points is obtained for eachfoot strike.

FIG. 1B is a medial side view diagram of an embodiment of a shoe 10 ofFIG. 1A. In this view, the shoe 10 is further shown to include a midsole12 and an outsole 11. The midsole 12 is constructed of one or morematerials that include, but is not limited to, Ethylene-vinyl acetate(EVA), poly (ethylene-vinyl acetate) (PEVA), rubber, carbon fiber, cork,etc.

The outsole 11 is constructed of one or more materials that include, butis not limited to, rubber, EVA, PEVA, TPU, carbon fiber, plastic, etc.For an athletic shoe, the outsole 11 includes a tread pattern for aparticular sport. For example, the tread pattern for a baseball shoeincludes plastic and/or metal cleats arranged to provide traction forrunning, throwing, hitting, and/or fielding in grass, in dirt, and/or onartificial surface. As another example, a training shoe will have atread pattern for weightlifting, cardio activities, etc. that occur on agym floor (e.g., wood, concrete, carpet, etc.).

FIG. 2 is a schematic block diagram of a cross-section an embodiment ofa shoe 10. As shown, the sole of the shoe 10 includes the outsole 11,the midsole 12, and/or an insole 13. The force detection system 20, orportion thereof, may be housed in the insole, the midsole, and/or theoutsole. For example, pressure sensors are housed in the insole and thecircuitry is housed in the midsole.

FIG. 3 is a schematic block diagram of an embodiment of force detectionsystem 20, 20-L, and/or 20-R that is capable of communicating with acomputing entity 35. A computing entity 35 includes one or morecomputing devices 40 as shown in one or more of FIGS. 5E through 5I. Thecomputing device 40 is implemented as shown in one or more of FIGS. 5Athrough 5F.

The force detection system 20 includes capacitor sensors 21, a drivesense module 22, digital filtering circuit 23, memory 24, a clockcircuit 25, a controller 26, a communication circuit 27, and a powersource 28. The capacitor sensors 21 are positioned within the shoe tosense pressure between a foot and the ground through the shoe. A forcedetection system 20 may include a few capacitor sensors per shoe toscores of capacitor sensors per shoe. Various embodiments of thecapacitor sensors and their positioning are discussed with reference toone or more of FIGS. 12-31, 33, and 34.

The drive sense module 22 includes a plurality of drive sense circuits,where a drive sense circuit is coupled to one or more capacitor sensors21 (e.g., variable capacitors). The drive sense circuit 22 providespower to a capacitor sensor and senses capacitance changes of the sensor21 due to pressure applied on the capacitor. An embodiment of the drivesense circuit 22 is described in greater detail with reference to FIG.4A.

The digital filtering circuit 23, which may be implemented by aprocessing module, converts digital signals it receives from a drivesense circuit 22 into a digital value that is representative of acharacteristic of the variable capacitor (e.g., impedance, capacitance,impedance change, capacitance change, etc.). The digital filteringcircuit 23 provides a digital value per sampling of the capacitor sensor21 to the memory 24 for storage therein.

The memory 24 includes volatile and/or non-volatile memory. The memoryalso stores operational instructions to enable the system 20 to senseand store data. The operational instructions may further include aninstruction set regarding the processing of stored capacitance data toproduce force data. Examples of converting capacitance data into forcedata will described with reference to one or more of the subsequentfigures.

The controller 26, which, in an embodiment, is implemented via aprocessing module as defined herein, coordinates the operation of theforce detection system 20. For example, the controller executes theoperational instructions that enable operation of the system. Inaddition, the controller 26 enables the clock circuit 25 to generate asampling clock, a real-time clock, and digital clock.

The sampling clock includes a crystal oscillator, or the like, toprovide a reference clock and further includes one or more phased lockedloops (PLL) to generate the desired clock signals. For example, theclock circuit generates the sampling clock to establish a rate forsampling the capacitor sensors. The sampling rate may equal the samplingclock, it may be a multiple of the sampling clock, or a fraction of thesampling clock.

The digital clock is used by the controller 26 and memory 24. Dependingon the amount of data to be stored and/or processed, the digital clockcan be set at a few MHz or hundreds of MHz or higher. It can also beadjustable to balance power consumption with data storage and/or dataprocessing efficiency.

The controller uses the real-time clock to timestamp the data beingstored in memory. The real time clock is synced with a reference realtime clock so that the foot force data and can time aligned with arecording of body movements.

The controller 26 instructs the communication circuit 27 to outputstored data from the memory 24 to the computing entity. Thecommunication circuit 27 is a wired and/or wireless transceiver. Forexample, a wired communication circuit 27 is an I²C (inter integratedcircuit) communication unit, an SPI (serial peripheral interface)communication unit, a CAN (controller area network) communication unit,a USB (universal serial bus) communication unit, a UART (universalasynchronous receiver/transmitter) communication unit, an IEEE 1394communication unit, etc. As another example, a wireless communicationcircuit 27 is a Bluetooth communication unit, a wireless local areanetwork communication unit, a Zigbee communication unit, a Z-wavecommunication unit, a low power wireless personal area network, a radiofrequency identification (RFID) communication unit, a near fieldcommunication unit, etc.

The power source 28 includes one or more batteries and provides power tothe other components of the system 20. The power source 28 may furtherinclude a power supply, a battery charger, a power harvesting circuit,and/or a power management module. The power supply functions to convertthe battery voltage into one or more DC voltages ranging from 0.5 voltsto 5 volts or more. The power supply may be implemented in a variety ofways. As an example, the power supply is a linear regulator. As anotherexample, the power supply is a buck power supply. As another example,the power supply is a boost power supply.

The power harvesting circuit may be implemented in a variety of ways andmay include a variety of implementations. In an example, the powerharvesting circuit functions to generate a DC voltage from one or moreradio frequency (RF) signals, such as a cell phone signal, a Bluetoothsignal, an RFID signal, etc. In another example, the power harvestingcircuit functions to generate a DC voltage from compression of apiezoelectric material in the shoe and the wearer applies force on theshoe. In another example, the power harvesting circuit functions togenerate a DC voltage from heat of the wearer.

FIG. 4A is a schematic block diagram of an embodiment of a drive sensecircuit 22 coupled to a variable capacitor 21-1 of the capacitivesensors 21. The drive sense circuit (DSC) 22 includes an operationalamplifier (op amp) 30, a feedback circuit 31, a dependent currentsource, and an analog-to-digital converter (ADC) 35. The op amp 30receives a reference signal 29, which as shown in FIG. 4B, includes a DCcomponent 33 and an oscillating component 34.

The magnitude and frequency of the oscillating component 34 varydepending on the desired resolution of sensing capacitance differencesand on achieving minimal power consumption. For example, since powerequals voltage times current, minimal voltage and minimal current areneeded for minimal power consumption. Voltage is tied to the granularityof sensing capacitance change and current is tied to the impedance ofthe capacitor and the voltage. With high signal-to-noise (SRN) of thedrive sense circuit and subsequent filtering, micro-voltages of changecan be detected. To have a current in the micro-amps, the frequency ofthe oscillating component is determined to provide an impedance of thecapacitor that produces a micro-volt scale change from a micro-amp scalecurrent source.

Returning to FIG. 4A, the op amp 30 ideally functions to force thevoltages on its inputs to be the same. Thus, the voltage on the inputcoupled to the variable capacitor 21-1 is the same as the voltage of thereference signal 29. Since no current flows into an op amp 30, thecurrent produced by dependent current source 32 flows into the variablecapacitor 21-1. As the impedance of the variable capacitor changes, thedependent current source 32, based on a signal from the feedback circuit31, produces a varying current to keep the voltage of the variablecapacitor matching that of the reference signal 29.

The feedback circuit 31, which includes one or more components toprovide a loop gain of unit to open loop, scales the output of the opamp 30 to provide the control signal to the dependent current source 32.The output of the op amp 30 is a voltage that represents the impedanceof the variable capacitor 21-1 and changes of the impedance. With theforce detection system 20, the variable capacitor changes it capacitancebased on pressure. In an embodiment, as pressure on the capacitorincreases, its capacitance increases (e.g., plates get closer togetherand/or dielectric changes), which decreases the capacitor's impedance.In another embodiment, as pressure on the capacitor decreases, itscapacitance decreases (e.g., plates get further apart and/or dielectricchanges), which increases the capacitor's impedance.

The analog to digital converter (ADC) 23 converts the output of the opamp 30 into unfiltered digital values. For a sigma delta ADC, thedigital values are a stream of one-bit digital values. The digitalfiltering circuit 23, which, in an embodiment, includes a bandpassfilter and a decimation filter, converts the stream of one-bit digitalvalues into digital words at a desired sampling rate. The digital wordsare stored in the memory 24.

FIG. 5A is a schematic block diagram of an embodiment of a computingdevice 40 that includes a plurality of computing resources. Thecomputing resource include a core control module 41, one or moreprocessing modules 43, one or more main memories 45, a read only memory(ROM) 44 for a boot up sequence, cache memory 47, a video graphicsprocessing module 42, a display 48 (optional), an Input-Output (I/O)peripheral control module 46, an I/O interface module 49 (which could beomitted), one or more input interface modules 50, one or more outputinterface modules 51, one or more network interface modules 55, and oneor more memory interface modules 54. A processing module 43 is describedin greater detail at the end of the detailed description section and, inan alternative embodiment, has a direction connection to the main memory45. In an alternate embodiment, the core control module 41 and the I/Oand/or peripheral control module 46 are one module, such as a chipset, aquick path interconnect (QPI), and/or an ultra-path interconnect (UPI).

Each of the main memories 45 includes one or more Random Access Memory(RAM) integrated circuits, or chips. For example, a main memory 45includes four DDR4 (4^(th) generation of double data rate) RAM chips,each running at a rate of 2,400 MHz. In general, the main memory 45stores data and operational instructions most relevant for theprocessing module 43. For example, the core control module 41coordinates the transfer of data and/or operational instructions betweenthe main memory 45 and the memory 56-57. The data and/or operationalinstructions retrieve from memory 56-57 are the data and/or operationalinstructions requested by the processing module or will most likely beneeded by the processing module. When the processing module is done withthe data and/or operational instructions in main memory, the corecontrol module 41 coordinates sending updated data to the memory 56-57for storage.

The memory 56-57 includes one or more hard drives, one or more solidstate memory chips, and/or one or more other large capacity storagedevices that, in comparison to cache memory and main memory devices,is/are relatively inexpensive with respect to cost per amount of datastored. The memory 56-57 is coupled to the core control module 41 viathe I/O and/or peripheral control module 46 and via one or more memoryinterface modules 54. In an embodiment, the I/O and/or peripheralcontrol module 46 includes one or more Peripheral Component Interface(PCI) buses to which peripheral components connect to the core controlmodule 41. A memory interface module 54 includes a software driver and ahardware connector for coupling a memory device to the I/O and/orperipheral control module 46. For example, a memory interface 54 is inaccordance with a Serial Advanced Technology Attachment (SATA) port.

The core control module 41 coordinates data communications between theprocessing module(s) 43 and the network(s) 14 via the I/O and/orperipheral control module 46, the network interface module(s) 55, and anetwork card 58 or 59. A network card 58 or 59 includes a wirelesscommunication unit or a wired communication unit. A wirelesscommunication unit includes a wireless local area network (WLAN)communication device, a cellular communication device, a Bluetoothdevice, and/or a ZigBee communication device. A wired communication unitincludes a Gigabit LAN connection, a Firewire connection, and/or aproprietary computer wired connection. A network interface module 55includes a software driver and a hardware connector for coupling thenetwork card to the I/O and/or peripheral control module 46. Forexample, the network interface module 55 is in accordance with one ormore versions of IEEE 802.11, cellular telephone protocols, 10/100/1000Gigabit LAN protocols, etc.

The core control module 41 coordinates data communications between theprocessing module(s) 43 and input device(s) 52 via the input interfacemodule(s) 50, the I/O interface 49, and the I/O and/or peripheralcontrol module 46. An input device 52 includes a keypad, a keyboard,control switches, a touchpad, a microphone, a camera, etc. An inputinterface module 50 includes a software driver and a hardware connectorfor coupling an input device to the I/O and/or peripheral control module46. In an embodiment, an input interface module 50 is in accordance withone or more Universal Serial Bus (USB) protocols.

The core control module 41 coordinates data communications between theprocessing module(s) 43 and output device(s) 53 via the output interfacemodule(s) 51 and the I/O and/or peripheral control module 46. An outputdevice 53 includes a speaker, auxiliary memory, headphones, etc. Anoutput interface module 51 includes a software driver and a hardwareconnector for coupling an output device to the I/O and/or peripheralcontrol module 46. In an embodiment, an output interface module 46 is inaccordance with one or more audio codec protocols.

The processing module 43 communicates directly with a video graphicsprocessing module 42 to display data on the display 48. The display 48includes an LED (light emitting diode) display, an LCD (liquid crystaldisplay), and/or other type of display technology. The display has aresolution, an aspect ratio, and other features that affect the qualityof the display. The video graphics processing module 42 receives datafrom the processing module 43, processes the data to produce rendereddata in accordance with the characteristics of the display, and providesthe rendered data to the display 48.

FIG. 5B is a schematic block diagram of an embodiment of a computingdevice 40 that includes a plurality of computing resources similar tothe computing resources of FIG. 2A with the addition of one or morecloud memory interface modules 60, one or more cloud processinginterface modules 61, cloud memory 62, and one or more cloud processingmodules 63. The cloud memory 62 includes one or more tiers of memory(e.g., ROM, volatile (RAM, main, etc.), non-volatile (hard drive,solid-state, etc.) and/or backup (hard drive, tape, etc.)) that isremoted from the core control module and is accessed via a network (WANand/or LAN). The cloud processing module 63 is similar to processingmodule 43 but is remoted from the core control module and is accessedvia a network.

FIG. 5C is a schematic block diagram of an embodiment of a computingdevice 40 that includes a plurality of computing resources similar tothe computing resources of FIG. 2B with a change in how the cloud memoryinterface module(s) 60 and the cloud processing interface module(s) 61are coupled to the core control module 41. In this embodiment, theinterface modules 60 and 61 are coupled to a cloud peripheral controlmodule 63 that directly couples to the core control module 41.

FIG. 5D is a schematic block diagram of an embodiment of a computingdevice 40 that includes a plurality of computing resources, whichincludes include a core control module 41, a boot up processing module66, boot up RAM 67, a read only memory (ROM) 45, a video graphicsprocessing module 42, a display 48 (optional), an Input-Output (I/O)peripheral control module 46, one or more input interface modules 50,one or more output interface modules 51, one or more cloud memoryinterface modules 60, one or more cloud processing interface modules 61,cloud memory 62, and cloud processing module(s) 63.

In this embodiment, the computing device 40 includes enough processingresources (e.g., module 66, ROM 44, and RAM 67) to boot up. Once bootedup, the cloud memory 62 and the cloud processing module(s) 63 functionas the computing device's memory (e.g., main and hard drive) andprocessing module.

FIG. 5E is schematic block diagram of an embodiment of a computingentity 16 that includes a computing device 40 (e.g., one of theembodiments of FIGS. 2A-2D). A computing device may function as a usercomputing device, a server, a system computing device, a data storagedevice, a data security device, a networking device, a user accessdevice, a cell phone, a tablet, a laptop, a printer, a game console, asatellite control box, a cable box, etc.

FIG. 5F is schematic block diagram of an embodiment of a computingentity 16 that includes two or more computing devices 40 (e.g., two ormore from any combination of the embodiments of FIGS. 2A-2D). Thecomputing devices 40 perform the functions of a computing entity in apeer processing manner (e.g., coordinate together to perform thefunctions), in a master-slave manner (e.g., one computing devicecoordinates and the other support it), and/or in another manner.

FIG. 5G is schematic block diagram of an embodiment of a computingentity 16 that includes a network of computing devices 40 (e.g., two ormore from any combination of the embodiments of FIGS. 2A-2D). Thecomputing devices are coupled together via one or more networkconnections (e.g., WAN, LAN, cellular data, WLAN, etc.) and preform thefunctions of the computing entity.

FIG. 5H is schematic block diagram of an embodiment of a computingentity 16 that includes a primary computing device (e.g., any one of thecomputing devices of FIGS. 2A-2D), an interface device (e.g., a networkconnection), and a network of computing devices 40 (e.g., one or morefrom any combination of the embodiments of FIGS. 2A-2D). The primarycomputing device utilizes the other computing devices as co-processorsto execute one or more the functions of the computing entity, as storagefor data, for other data processing functions, and/or storage purposes.

FIG. 5I is schematic block diagram of an embodiment of a computingentity 16 that includes a primary computing device (e.g., any one of thecomputing devices of FIGS. 2A-2D), an interface device (e.g., a networkconnection) 70, and a network of computing resources 71 (e.g., two ormore resources from any combination of the embodiments of FIGS. 2A-2D).The primary computing device utilizes the computing resources asco-processors to execute one or more the functions of the computingentity, as storage for data, for other data processing functions, and/orstorage purposes.

FIGS. 6A-6C are a medial side, top view, and lateral side view diagramsof an embodiment of force detection system 20 implemented in the sole ofa shoe. The force detection system 20 includes a layer of variablecapacitors 100, a layer of compression plates 102, and a circuitrysection 104. The layer of variable capacitors 100 and the layer ofcompression plates 102 are positioned within the variable capacitorsection 106.

The circuitry section 104 includes the circuit components of the forcedetection system 20 as shown in FIG. 3, excluding the capacitor sensors21. The circuit components may be discrete components and/or included inan integrated circuit (IC). For example, the drive sense circuits anddigital filtering circuitry are implemented as an integrated circuit.The circuitry components, as ICs and/or discrete components, are mountedon one or more circuit boards (e.g., rigid and/or flexible) that fitwithin the circuitry section 104.

The capacitor sensors 21 include the layer of variable capacitors 100and the layer of compression plates 102. The compression plates arepositioned closer to the foot than the variable capacitors. When a forceis applied to a compression plate as a result of a person wearing ashoe, the compression plate pushes on a set of variable capacitors. Themagnitude and angle of the force applied to the compression plate iscalculable based on the changes to the capacitances of the set ofvariable capacitors. One or more examples will be described withreference to at least one subsequent figure.

FIGS. 6D-6F are a medial side, top view, and lateral side view diagramsof an embodiment of force detection system 20 implemented in the sole ofa shoe. The force detection system 20 includes a first layer of variablecapacitors 100, a second layer of variable capacitors 108, and acircuitry section 104. The first and second layers of variablecapacitors 100 and 108 are positioned within the variable capacitorsection 106. The circuitry section 104 includes the circuit componentsof the force detection system 20 as shown in FIG. 3, excluding thecapacitor sensors 21, as previously discussed.

The capacitor sensors 21 include the first and second layers of variablecapacitors 100 and 108. The first layer of variable capacitors ispositioned closer to the foot than the first layer of variablecapacitors. When a force is applied to a variable capacitor of the firstlayer as a result of a person wearing a shoe, the first layer variablecapacitor pushes on a set of second layer variable capacitors. Themagnitude and angle of the force applied to the first layer variablecapacitor is calculable based on the changes to the capacitances of thefirst layer variable capacitor and set of second layer variablecapacitors. One or more examples will be described with reference to atleast one subsequent figure.

FIGS. 7A-7C are a medial side, top view, and lateral side view diagramsof an embodiment of force detection system 20 implemented in the sole ofa shoe. The force detection system 20 includes a layer of variablecapacitors 100 and a circuitry section 104. The layer of variablecapacitors 100 is positioned within the variable capacitor section 106.The circuitry section 104 includes the circuit components of the forcedetection system 20 as shown in FIG. 3, excluding the capacitor sensors21, as previously discussed.

The capacitor sensors 21 include the layer of variable capacitors 100.When a force is applied to a set of variable capacitors as a result of aperson wearing a shoe, the set of variable capacitors are compressed.The magnitude and angle of the force applied to the set of variablecapacitors is calculable based on the changes to the capacitances of theset of variable capacitors. One or more examples will be described withreference to at least one subsequent figure.

FIGS. 8A-8C are front, side, and top views of an example of forceapplied by a foot to the force detection system 20 when a wearer isstanding. With a wearer standing, the force applied to the shoe isnormal to the ground in the front view and in the top view, and it isdistributed between the forefoot and the heel. The force applied to theshoe is weight & muscle contraction of the wearer and is represented bya red arrow. With the wearer standing, there is little to no musclecontraction force, thus the force is primarily a weight force.

The weight force traverses through the insole 13, the midsole 12, andthe outsole 11 of a shoe to the ground 110. The ground pushes back withan equal and opposite force with ground reaction force, which isrepresented by a green arrow. To help illustrate the mirroring nature ofthe weight and muscle contraction force and the ground reaction force,the complementary colors of green and red are used.

In the side view of FIG. 8, the midsole 12 includes an angular sectionthat slopes upward from the toes to the heel. The angular sectionshifts, from the side view perspective, how the weight and musclecontraction force traverses through the shoe to the ground 110. Asshown, the red weight and muscle contraction force is at an angle toground. The angle of the force is orthogonal to the angle of the midsole12. The green ground reaction force is equal and opposite to the weightand muscle contraction force and includes a commentary angle.

With the force detection system 20 implemented in the sole of the shoe(e.g., in the insole, midsole, and/or outsole), the magnitude anddirection of the weight and muscle contraction force and the groundreaction force can be determined. This is a vast improvement overconventional foot force analysis systems that only measure thenormalized magnitude of the force (i.e., the resulting Z component ofthe force), not the true magnitude of the force. Examples of computingthe magnitude and direction of the forces will be discussed withreference to one or more subsequent figures.

FIGS. 9A-9C are front, side, and top views of an example of forceapplied by a foot to the force detection system 20 when a wearer isexecuted a lateral push-off. A wide variety of athletes execute alateral push-off in playing their respective sport. For example, agolfer executes a lateral push-off on the back leg during the backswingand down swing and then on the front leg during the follow through. Abaseball player goes through a similar lateral push-off for hitting andfor pitching. A tennis player uses a lateral push-off to hit a tennisball, but also to stop or change directions while running. A footballplayer, a soccer player, an ice hockey player, and a skier all use alateral push-off to stop and/or to change direction of movement.

In this example, the majority of the weight and muscle contraction forceis in the ball of the foot with none shown in the heel section. Notethat some athletes may executed a lateral push-off with up to half oftheir weight in the heel section.

For a lateral push-off the weight and muscle contraction force, asrepresented by the red arrow, traverses down the leg towards the foot.For an athletic movement, the athlete is contracting his or her muscles,which adds up to six times the athlete's body weight to the overallweight and muscle contraction force. Assuming the shoe is firmly plantedon the ground (i.e., no roll over or slipping), the weight and musclecontraction force is divided into perpendicular force components asrepresented by the blue arrows and parallel force components asrepresented by the yellow arrows in the y direction and orange arrows inthe x direction at the foot and into the shoe.

Within the shoe, the perpendicular Z force component traverses throughthe shoe to the ground. The ground produces the ground reaction force,which is represented by the green arrow, that is equal to and oppositeof the perpendicular Z force. In this example, the ground reaction forceis not equal to and opposite of the weight and muscle contraction force,but of the perpendicular Z component, which is less than the weight andmuscle contraction force. The magnitude of the perpendicular Z componentis calculated the cosine of φ times the magnitude of the weight andmuscle contraction force. “φ” represents the angle of the weight andmuscle contraction force with respect the slopes of the sole in the ydirection and in the x direction. In this example, the sole has nomedial to lateral slope and has a slight toe to heel slope.

The horizontal y component, as expressed by the yellow arrow in thefront view and top view, is parallel to the surface of the sole and tothe ground. If the shoe does not include a mechanism to apply a forcethat is equal and opposite of the horizontal y component, the foot willmove laterally within the shoe, which increases the angle and reducesthe ground reaction force.

The horizontal x component, as expressed by the orange arrow in the sideview and top view, is parallel to the surface of the sole and at aslight angle to the ground. If the shoe does not include a mechanism toapply a force that is equal and opposite of the horizontal x component,the foot will move linearly within the shoe, which increases the angleand further reduces the ground reaction force.

The force detection system 20 is operable to detect the magnitude andangles of the ground reaction force, the perpendicular Z forcecomponent, the horizontal Y force component, and the horizontal X forcecomponent. From these data points, the weight and muscle contractionforce can be calculated.

FIGS. 10A-10C are front, side, and top views of an example of forceapplied by a foot to the force detection system 20 when a wearer isrunning and the foot is impacting the ground. In an efficient sprint,the first contact of the landing foot should almost be directlyunderneath the athlete. The athlete pulls his or her leg back afterinitial contact of the foot until the foot is released from the ground.How the foot engages the ground and the duration of ground impact effectthe efficiency of running.

In this example, the weight and muscle contraction force is shown for aninefficient runner since the contact point with the ground is in frontof the body as evidenced by the angle of the force. Further, the exampleillustrates the weight and muscle contraction force only has an angle inthe linear direction and not one in the lateral to medial direction.

The weight and muscle contraction force, as represented by the redarrow, traverses down the leg towards the foot. For a stride impact whenrunning, the athlete is contracting his or her muscles and landing onthe ground, which adds up to six times the athlete's body weight to theoverall weight and muscle contraction force. Assuming the shoe is firmlyplanted on the ground (i.e., no roll over or slipping), the weight andmuscle contraction force is divided into perpendicular force componentsas represented by the blue arrows and parallel X force components asrepresented by the orange arrow in the x direction at the foot and intothe shoe.

Within the shoe, the perpendicular Z force component traverses throughthe shoe to the ground. The ground produces the ground reaction force,which is represented by the green arrow, that is equal to and oppositeof the perpendicular Z force. In this example, the ground reaction forceis not equal to and opposite of the weight and muscle contraction force,but of the perpendicular Z component, which is less than the weight andmuscle contraction force. The magnitude of the perpendicular Z componentis calculated the cosine of φ times the magnitude of the weight andmuscle contraction force. “φ” represents the angle of the weight andmuscle contraction force with respect the slopes of the sole in the xdirection. In this example, the sole has no medial to lateral slope andhas a slight toe to heel slope.

The horizontal x component, as expressed by the orange arrow in the sideview and top view, is parallel to the surface of the sole and at aslight angle to the ground. If the shoe does not include a mechanism toapply a force that is equal and opposite of the horizontal x component,the foot will move linearly within the shoe, which increases the angleand further reduces the ground reaction force.

The force detection system 20 is operable to detect the magnitude andangles of the ground reaction force, the perpendicular Z forcecomponent, the horizontal Y force component (if any), and the horizontalX force component. From these data points, the weight and musclecontraction force can be calculated.

FIGS. 11A-11F are schematic block diagrams of another example of forcesapplied by a foot to the force detection system when a person isrunning. In the examples of FIGS. 11A through 11F, the relationshipbetween the weight and muscle contraction force, the z force component,and the x force component vary based on where the foot to ground contactis for a stride.

In FIG. 11A, the foot is making initial contact with the ground for agiven stride. This is similar to the foot-ground connection discussedwith reference to FIGS. 10A-10C. In the remaining figures, thefoot-ground contact varies as the runner executes the stride. Withineach figure, the relationship between weight and muscle contractionforce, the Z force component, and the X force component varies.

With the high sampling rate of the force detection system 20 (e.g., 5KHz or more), dozens to hundreds of samples are obtained for a singlefoot strike. This provides a level of granularity to better understandhow the foot engages with the ground during a running. It furtherenables identifying efficiencies and inefficiencies in running. Withinefficiencies identified, corrective measures can be determined toimprove a runner's form and/or running efficiency.

FIG. 12 is a schematic block diagram of another embodiment of a layer ofvariable capacitors and a layer of compression plates of a forcedetection system 20. In this example, the compression plates 120 arerepresented by green discs. A variable capacitor includes one or moreconductive layers, two or more insulating layers, and two connections(i.e., capacitor plates). In this example, the insulating layers arerepresented as yellow disc shapes, the conductive layers are representedas blue disc shapes, and the connectors are represented as blackring-like, or plate-like, shapes.

The compression plates 120 may be comprised of one or more materials toform a rigid structure. For example, the compression plates arecomprised of plastic. As another example, the compression plates arecomprised on fiberglass. As another example, the compression plates arecomprised on carbon fiber. As yet another example, the compressionplates are comprised on a metal.

The dimensions of a compression plate will vary depending on thematerial, or materials, it is comprised of, the size of the variablecapacitors, the distance between the variable capacitors, the number ofvariable capacitors it overlaps, and a maximum force load. For example,the thickness of a compression plate, which should be in the range of afew microns to a few millimeters, is based on the rigidity of thematerial, the maximum force load, and a flexion range of the compressionplate under a force load. Ideally, the flexion of the compression plateshould be negligible with respect to the compression range of thevariable capacitors. In the ideal case, the flexion of the compressionplate can be ignored when calculating the applied force; thecalculations will be based on the compression of the variablecapacitors. If the flexion of the compression plate is not negligible,the flexion should be factored into the calculations of the appliedforce, which makes the calculations more complex than in the ideal case.

The perimeter dimension of a compression plate should be comparable tothe perimeter of the variable capacitors the compression plate overlaps.For example, a compression plate, which overlaps three variablecapacitors having a circular shape from a top perspective, has acircular shape with a diameter in the range of 1.25 times to 2.25 timesthe diameter of a variable capacitor. As another example, a compressionplate, which overlaps three variable capacitors having a circular shapefrom a top perspective, has a rounded equilateral triangular shape witheach of a base dimension and of a height dimension of 1.25 times to 2.25times the diameter of a variable capacitor.

For a variable capacitor, the number of conductive layers and the numberof insulator layers depend on the desired capacitance range, desiredthickness of the layer of capacitors, and the materials of composition.A variable capacitor may be fabricated in a variety of ways. Forexample, a variable capacitor is fabricated from a Z electrometricconductor (ZEC). In another example, a variable capacitor is fabricatedfrom one or more dielectric elastomers. The capacitance value and therange of capacitance values varies based on the materials used and theircompression ratio. The materials include acrylates, silicones,polyurethanes (PU), rubbers, latex rubbers, acrylonitrile butadienerubbers, olefinic, polymer foams, fluorinated and styrenic copolymers,etc.

The equation for a parallel capacitor is:

$C = {\epsilon_{0}\epsilon_{r}\frac{A}{d}}$

Where C is the capacitance, ε₀ is the permittivity of a vacuum, ε_(r) isthe relative permittivity, A is the area of the plates, and d is thedistance between the plates. The relative permittivity can range from 1to 10 or more.

In an example, a variable capacitor is formed with a compressibledielectric material layer between two conductive plates that areseparated by a distance from each other. The variable capacitor mayfurther include two non-compressive insulting layers. The dielectricmaterial has a relative permittivity of 2.8 and is compresses by 50%from no compression to fully compressed, which occurs at 825 kg(kilograms) of force.

For this example, the two conductive plates have an area of 71.26millimeters squared (mm²) (i.e., ⅜ inch diameter) and the uncompresseddistance between the plates of 0.79 mm (i.e., 1/32 of an inch). In theuncompressed state, the variable capacitor has a capacitance value of2.25 pico Farads (pF). When the distance between the plates compressesby 50%, the variable capacitor has a capacitance of 4.45 pF. To increasethe capacitance, the variable capacitor includes 4 conductive, ordielectric layers, separated by insulating layer and are coupled inparallel to provide a compressed capacitance of 8.9 pF and a compressedcapacitance of 17.8 pF. With a four conductive layer variablecapacitance, its total thickness would be about 3.5 to 4.3 mm thick;less than the thickness of a conventional insole.

For a weight sensing range of 0 kg to 825 kg, the variable capacitorwill correspondingly range from no compression to fully compressed. Thevariable capacitor's capacitance value to compress level curve isfactored into the determination of a weight force causing a currentcompression of the capacitor. If the capacitance value to compress levelis fairly linear, then the capacitance value for a particular sample canbe multiplied by a constant to obtain a weight force value. If thecapacitance value to compress level is not linear, then a non-linearequation will be applied to the capacitance value to obtain acorresponding weight force value.

For this example, assume that the desired granulating for weight forcechanges is 0.5 kg, then, for a range of 0 to 825 kg, there are 1650different values of capacitances that need to be measured. As such, acapacitance difference of 0.005 pF represents a 0.5 kg difference.

Continuing with the example and with respect to the drive sense circuit,a 50 mV (milli volt) sinusoidal signal having a frequency of 100 kHz isused as the reference signal, offset by the DC component. The impedanceof a capacitor is expressed as:

$z = \frac{1}{2\pi fC}$

Where z is the impedance, f is the frequency of the reference signal,and C is the capacitance value. For the uncompressed capacitance valueof 8.9 pF, the impedance is 179 K Ohms. Since I=V/Z, the currentsupplied by the drive sense circuit is 276 nA (nano Amps), yielding apower of 13.9 nW (nano Watts).

To sense a 0.5 kg change in the weight force, the drive sense circuitneeds to detect a 0.0054 pF capacitance change, which, for the 50 mVreference signals, corresponds to a current change of 169 nA (e.g.,1.69*10⁻¹⁰ amps). The assignee's drive sense circuit has asignal-to-noise ration of at least 120 dB, which means in can detect achange at a ratio of 1 to 1*10¹². As such, the assignee's drive sensecircuit is more than sensitive enough to detect a 169 nA change.

With a 120 dB or more of signal to noise ratio, there is ample room toadjust capacitor size and shape, the magnitude of the reference signal,the number of capacitors in the force detection system, and so on. Forexample, the shape of the capacitor from a top perspective is a four,five, six, seven, eight, or more, sided polygon. The compression platewould have a corresponding shape from the top perspective. Examples ofhow the compression plate effects the capacitance values of thecapacitors it compresses will be discussed with reference to one or moresubsequent figures.

FIG. 13 is a schematic block diagram of another embodiment of a layer ofvariable capacitors of FIG. 12 without a layer of compression plates.Within an area of the force detection system, a group of variablecapacitors are arranged as rows and columns. The positioning of avariable capacitor in a group and variable capacitors and within theforce detection system allows the forces it senses to be equated to aportion of a foot of a wearer.

FIGS. 14A-14C are schematic block diagrams of an example of a layer ofvariable capacitors 100 and a layer of compression plates 102 of a forcedetection system. FIG. 14A illustrates a top view of the layer ofcompression plates 102 only, which are represented by green circles.FIG. 14B illustrates a top view of the layer of variable capacitors 100only, which are represented by blue circles. FIG. 14C illustrates a topview of the layer of compression plates 102 (i.e., partially translucentgreen circles) position over the layer of variable capacitors 100 (i.e.,the blue circles). In this example, one compression plate overlaps threevariable capacitors. When a force is applied to the compression plate,it transfers the force to the three variable capacitors. The forceapplied to each of the variable capacitors is measured and used todetermine the magnitude and direction of the force on the compressionplate.

FIGS. 15A-15E are schematic block diagrams of an example of a layer ofvariable capacitors 100 and a layer of compression plates 102 of a forcedetection system with and without compression of the capacitors. FIG.15A illustrates the variable capacitors 100-1 in a non-compress state(i.e., no force is being applied to the compression plate 102-1) andFIG. 15B illustrates the variable capacitors 100-1 in a fully compressedstate (i.e., maximum force is being applied to the compression plate102-1).

The variable capacitors 100-1, with the blue conductive layers and theyellow insulating layers, are held in place by a capacitor (cap) holdingstructure 134. The cap holding structure 134 is comprised of a flexiblematerial that allows the capacitors to expanding horizontally and theyare compressed vertically while staying in place. For example, the capholding structure 134 is comprised of one or more of rubber, silicon,EVA, PEVA, foam, a gel, etc.

The compression plates 102-1 (e.g., the green discs) are held in placeby a plate holding structure 130. The plate holding structure 130 iscomprised of a flexible material that allows for each compression plateto move freely and independently. The plate holding structure 130 iscomprised of one or more of rubber, silicon, EVA, PEVA, foam, a gel,etc.

The variable capacitors 100-1, the cap holding structure 134, thecompression plates 102-1, and the plate holding structure 130 are housedwithin a perimeter support structure 132. The perimeter supportstructure 132 is comprised of a rigid material and may house one or moresets of a compression plate and associated variable capacitors. As forthe rigid material, it is one or more of a hard rubber, plastic, carbonfiber, etc.

In an example as shown in FIG. 15C, the perimeter support structure 132houses one set of a compression plate and associated variablecapacitors. In this example, the force detection system 20 would includea plurality of perimeter support structures 132. In another example asshown in FIG. 15D, the perimeter support structure 132 houses two setsof a compression plate and associated variable capacitors. In yetanother example as shown in FIG. 15E, the perimeter support structure132 houses three sets of a compression plate and associated variablecapacitors.

FIGS. 16A-16C are schematic block diagrams of examples of a geometricand electrical relationship between variable capacitors of a secondlayer and a compression plate of a first layer within a force detectionsystem. FIG. 16A illustrates from a top view, a circular compressionplate 102-1 that partially overlaps three variable capacitors 100-1(e.g., C2, C3, and C4). FIG. 16B illustrates from a top view, atriangular compression plate 102-1 that substantially overlaps threevariable capacitors 100-1 (e.g., C2, C3, and C4).

FIG. 16C illustrates a schematic block diagram of the three variablecapacitors of FIGS. 16A and 16B coupled to respective drive sensecircuits (DSC). One plate of each of the capacitors C2-C4 is coupled toa reference ground and the other plate is coupled to a respective DSC.The output of each drive sense circuit is a digital value, at a desiredsampling rate, of the capacitance of the respective capacitor. Forexample, one of the DSCs outputs a digital value of the capacitancevalue for C2; another of the DSCs outputs a digital value of thecapacitance value for C3; and third one of the DSCs outputs a digitalvalue of the capacitance value for C4.

FIG. 17 is a schematic block diagram of an example of a graph thatdepicts capacitance variance with respect to compression of a ofvariable capacitor. In this example, as force is applied to a variablecapacitor, the capacitance increases. When no force is applied, thecapacitance is at a minimum capacitance value. The capacitance valueincreases with force until it reaches a maximum value. At this point,the variable capacitor is fully compressed and a further increase inforce will not increase the capacitance.

For an ideal variable capacitor, its capacitance changes linearly withthe force applied. For many variable capacitors, there is at least arange of capacitance values where the change in force is substantiallylinear. As such, the applied force can be accurately determined based onthe measured capacitance for the range of capacitances.

In equation form, C₀=C_(min)Δx*ΔC, where C₀ is the capacitance of thevariable capacitor; C_(min) is the capacitance of the variable capacitorwith no compression, Δx is the percentage of displacement with respectto a maximum displacement (i.e., compression), where Δx=x₀/x_(max), andΔC is the difference between C_(max) and C_(min). Also, the force tocompress the variable capacitor is expressed as F=k*x₀, where F is theforce, k is the compression factor of the variable capacitor, and x isthe displacement. The compression factor “k” is a constant that reflectsthe stiffness of the variable capacitor (i.e., its resistance tocompression).

Through substitution:

$F = {\frac{k*x_{\max}}{\Delta C}*\left( {C_{0} - C_{\min}} \right)}$

In this form, the applied force is readily calculated from a measuredcapacitance (C₀) of the variable capacitor on a per sampling rate basis.The forces measured by multiple variable capacitors can be used todetermine the magnitude and direction of the force applied to acorresponding compression plate. Note that non-linearities between forceand capacitance value can be factored into the above equation. In suchnon-linear applications, k is not a constant but a variable thatrepresents the shape of the curve.

FIGS. 18A-18C are schematic block diagrams of examples of an impactforce applied to a cell of a force detection system (e.g., a compressionplate and three variable capacitors). In this example, the variablecapacitors C2-C4 are substantially identical in terms of size, shape,compression factor (k), minimum capacitance, maximum displacement, andmaximum capacitance. As such, when an equal force is applied to thevariable capacitors, they each produce a capacitance value that aresubstantially identical (i.e., negligible differences).

FIGS. 18A and 18B illustrate a top view and a side view of a force beingapplied to the cell. The force is normal to the compression plate 102-1,which transfers the force equally among the variable capacitors C2-C4,as shown in FIG. 18C. FIG. 18C is also applicable for a cell embodimentthat does not include a compression plate; it includes, for example thethree variable capacitors provided that the wearer's foot makes contactwith the variable capacitors.

With the force equally applied to the capacitors, they each have thesame capacitance change. The force applied to each capacitor is thenreadily calculatable. The magnitude and direction of the applied forceis then calculated from the forces detected by the capacitors. Anexample of the calculation will be discussed with reference to one ormore of FIGS. 19A-24B.

FIGS. 18D-18F are schematic block diagrams of examples of an impactforce applied to a cell of a force detection system (e.g., a first layercapacitor and three second layer capacitors). In this example, the toplayer is another variable capacitor. In this instance, the magnitude ofthe applied force is calculable from the capacitance change of the firstlayer capacitor 108-1 and the direction is calculable from thecapacitance change of the second layer capacitors 100.

FIGS. 19A-19B are schematic block diagrams of an example of determininga normal vector of a reference plane of a cell of a force detectionsystem in response to an impact force, wherein the normal vectorcorresponds to the impact force yielding x, y, and z direction forcedata. From the examples of FIGS. 18A-18F, the second layer of variablecapacitors (C2-C4) yield a corresponding force vector f_C2 through f_C4that are equal as shown in FIG. 19A.

The force vectors are used to create a reference plane as shown in FIG.19B, which is then used to determine a normal vector that represents themagnitude and direction of the applied force. To calculate the referenceplane, the force vectors f_C2 through f_C4 are mapped to a coordinatesystem (e.g., a Cartesian system or a polar system, this example isbased on a Cartesian coordinate system). In this example, the x-y planeof the Cartesian coordinate system is parallel to the bottom of a shoeand the z direction is perpendicular to the bottom of the shoe.

As shown, f_C2 is mapped to a coordinate point of x2, y2, z2; f_C3 ismapped to a coordinate point of x3, y3, z3; and f_C4 is mapped to acoordinate point of x4, y4, z4. The three coordinate points are used todetermine the reference plane. For example, the equation of a plane ofD=Δx+By+Cz. Coefficients A, B, and C are determined such that eachcoordinate point (e.g., coordinate points of C2, C3, and C4) on theplane satisfies this equation.

As a specific example, assume that coordinate point C2 is 1, 1, 1;coordinate point C3 is 2, 3, 1; and coordinate point C4 is 4, 2, 1. Fromthese coordinate points, three equations emerge.

1A+1B+1C=D for coordinate point C2;

2A+3B+1C=D for coordinate point C3; and

4A+2B+1C=D for coordinate point C4.

Solving the three equations yields A=0; B=0; and C=1. From the planeequation of D=(1)z, the normal vector of the plane is calculable. Forexample, equation for the normal vector (n)=Ai+Bj+Ck, where i is theunity vector in the x direction, j is the unity vector in the ydirection, and k is the unity vector in the z direction. Thus, for thisexample the normal vector (n) (i.e., the applied force)=(1)k, whichmeans that the applied force has a magnitude of 1 and a direction thatis perpendicular to the x-y plane.

FIGS. 20A-20D are schematic block diagrams of another example ofdetermining a normal vector of a reference plane of a cell of a forcedetection system. In this example, the applied force on a cell (e.g., aset of variable capacitors and a compression plate) is at angle from thez axis with respect to both the x and y. An example is shown the topview perspective of FIG. 20A. The impact force, as represented by theorange arrow includes an x force component that is represented by thered arrow and a y-force component that is represented by the yellowarrow.

FIG. 20B is a side view from an x-z plane of the cell that depicts itbeing impacted by the x-force (i.e., the red arrow). The x-force pusheson the compression plate causing it to slant in the direction of thex-force. This causes more compression of capacitor C2 than of capacitorC4, which compresses more that capacitor C3.

FIG. 20C is a side view from a y-z plane of the cell that depicts itbeing impacted by the y-force (i.e., the yellow arrow). The y-force ismore vertical than the x-force, thus it pushes on the compression platemore perpendicularly, which causes a more even distribution of the forceamong the capacitors. Even so, there is a bit more force applied tocapacitor C4 than capacitors C2 and C3. With respect to both FIGS. 20Band 20C, capacitor C2 has the more force applied to it than capacitorC4, which has more forced applied to it than capacitor C3. As such, thecapacitance value for C2, will be higher than the value for C4, whichwill be higher than the value for C3.

FIG. 20D illustrates an example of a reference plane resulting from theimpact force (e.g., the orange arrow). For this example, assume thatcoordinate point C2 is 1, 1, 4; coordinate point C3 is −1, 2, 1; andcoordinate point C4 is 1, 2, 3. From these coordinate points, threeequations emerge.

1A+1B+4C=D for coordinate point C2;

−1A+2B+1C=D for coordinate point C3; and

1A+2B+3C=D for coordinate point C4.

Solving the three equations yields A=−¼; B=¼; and C=¼. From the planeequation of 1=−(¼)x+(¼)y+(¼)z, the normal vector of the plane iscalculable. For example, equation for the normal vector (n)=Ai+Bj+Ck,where i is the unity vector in the x direction, j is the unity vector inthe y direction, and k is the unity vector in the z direction. Thus, forthis example the normal vector (n) (i.e., the appliedforce)=−(¼)i+(¼)j+(¼)k. The impact force is equal to and opposite of thenormal vector.

FIGS. 21A-21D are schematic block diagrams of another example ofdetermining a normal vector of a reference plane of a cell of a forcedetection system. In this example, the applied force on a cell (e.g., aset of variable capacitors and a first layer capacitor) is at angle fromthe z axis with respect to both the x and y. An example is shown the topview perspective of FIG. 21A. The impact force, as represented by theorange arrow includes an x force component that is represented by thered arrow and a y-force component that is represented by the yellowarrow.

FIG. 21B is a side view from an x-z plane of the cell that depicts itbeing impacted by the x-force (i.e., the red arrow). The x-force pusheson the first layer capacitor 108-1 causing it to slant in the directionof the x-force. This causes more compression of capacitor C3 than ofcapacitor C4, which compresses more than capacitor C2. With the angle ofthe x-force, the compression of capacitor C3 is slightly greater thanthat of capacitor C4.

FIG. 21C is a side view from a y-z plane of the cell that depicts itbeing impacted by the y-force (i.e., the yellow arrow). The y-force hasapproximately the same angle as the x-force, thus it pushes on the firstlayer capacitor in a similar manner. This causes more compression ofcapacitor C4 than of capacitors C3 and C2. With the angle of thex-force, the compression of capacitors C3 and C2 are comparable.

With respect to both FIGS. 21B and 21C, capacitor C3 has the more forceapplied to it than capacitor C4, which has more forced applied to itthan capacitor C3. As such, the capacitance value for C2, will be higherthan the value for C4, which will be higher than the value for C3.

FIG. 21D illustrates an example of a reference plane resulting from theimpact force (e.g., the orange arrow) through the first layer capacitorto the second layer of capacitors. The capacitance change of the firstlayer capacitor in combination with the second layer capacitorsdetermines the magnitude and direction of the impact force. For thisexample, assume that coordinate point C2 is 2, 1, 1; coordinate point C3is 0, 0, 5; and coordinate point C4 is 1, −1, 4. From these coordinatepoints, three equations emerge.

2A+1B+1C=D for coordinate point C2;

5C=D for coordinate point C3; and

1A+(−1)B+4C=D for coordinate point C4.

Solving the three equations yields A=⅓; B= 2/15; and C=⅕. From the planeequation of 1=(⅓)x+( 2/15)y+(⅕)z, the normal vector of the plane iscalculable. For example, equation for the normal vector (n)=Ai+Bj+Ck,where i is the unity vector in the x direction, j is the unity vector inthe y direction, and k is the unity vector in the z direction. Thus, forthis example the normal vector (n) (i.e., the applied force)=(⅓)i+(2/15)j+(⅕)k. The direction of the impact force is opposite of the normalvector and its magnitude is the sum of the magnitude of the normalvector and the force determined from the compression of the top layercapacitor.

FIGS. 22A-22C are schematic block diagrams of an example of determininga plurality of normal vectors of a plurality of reference planes of aplurality of cells of a force detection system in response to an impactforce. FIG. 22A illustrates twelve second layer variable capacitors(C1-C12) arranged in a pattern to form 12 triangles, which representindependent reference planes. In this example, the impact force is shownas an orange arrow that applies a force to the variable capacitors atdifferent levels creating a force pattern as shown in FIG. 22B.

For each reference plane a normal force is determined as previouslydiscussed. In an example, the magnitude and direction of the impactforce is determined from resulting normal vectors. As a specificexample, the normal vectors are added together to produce a final normalvector. The impact force is equal to and opposite of the final normalvector. In another example, the twelve normal vectors are used todetermine twelve impact force components to produce an impact forcegradient.

FIG. 23 is a schematic block diagram of an example of two cells for aforce detection system. Each includes a top layer capacitor (TC) (lightgreen) and four lower layer capacitors (green, blue, red, black). In thefirst cell, the top layer capacitor TC1 substantially overlaps the fourlower layer capacitors (C1-C4), where C1 is the blue shaded capacitor,C2 is the red shaded capacitor, C3 is the green shaded capacitor, and C4is the black shaded capacitor. In the second cell, the top layercapacitor TC2 substantially overlaps the four lower layer capacitors(C5-C8), where C5 is the blue shaded capacitor, C6 is the red shadedcapacitor, C7 is the green shaded capacitor, and C8 is the black shadedcapacitor. There is a gap of a few microns to a millimeter or morebetween the lower layer capacitors to allow for horizontal expansionfrom a vertical compression.

FIGS. 24A-24B are schematic block diagrams of examples of impact forcesimpacting a cell of FIG. 23. FIG. 24A is a front view of the first cellof FIG. 23. The cell is receiving a perpendicular force via an object.In this example, the object has a rounded outer shape resembling a crosssection of a toe.

The top layer capacitor TCI is sandwiched between two compressionplates. The first compression plate receives the impact force applied bythe object. The impact area is small due to the shape of the object. Thefirst compression plate transfers the impact force to the top layercapacitor TC1 in a three-dimension parabolic pattern. The force appliedto the top layer capacitor TC1 is the largest and decreases in aparabolic manner the further away from the impact force area it gets.While this produces a nonlinear force gradient applied to the top layercapacitor TC1, the change is change in capacitance is measured as asingle value to represent an average, or median, force.

The top layer capacitor TC1, as it is compressed, applies the parabolicforce gradient to the second compression plate. The second compressionplate transfers the parabolic force gradient to the lower layercapacitors (C1-C4). Each of the lower layer capacitors are compressedbased on the force it receives. The capacitance change is used todetermine the individual forces received by the lower layer capacitors.The combination of the capacitance changes to TC1 and to C1-C4 are usedto determine the magnitude and direction of the impact force.

FIG. 24B is another front view of the first cell of FIG. 23. In thisexample, the top compression plate is receiving an impact force (e.g.,the orange arrow) at an angle. As such, in this plane of view, theimpact force includes an x force component (e.g., the yellow arrow) anda y force component (e.g., the red arrow). The impact force, and its xand y components, traverse through the cell. Due to the angle of theimpact force, more force is transferred to C4 (e.g., the black shadedcapacitor) than to C3 (the green shaded capacitor). As such, C4 willhave a greater capacitance change than C3. The combination ofcapacitance changes of TC1 and C1 through C4 are used to calculate themagnitude and direction of the impact force as previously discussed.

As an alternative embodiment, a cell includes one compression plate andthe four lower capacitors, omitting the top compression plate and thetop layer capacitor. In another alterative embodiment, a cell includesthe top layer capacitor and the four lower layer capacitors, omittingthe compression plates.

FIG. 25 is a schematic block diagram of an example of a plurality ofcells. Each cell includes three or more lower-level capacitors. Fourshown in this example: C1=blue, C2=red, C3=green, and C4=black). Thecell may further includes a top layer capacitor and/or one or morecompression plates. In this example, the cell includes a top layercapacitor and two compression plates as shown in FIGS. 24A and 24B.

The cells are arranged in rows and columns. In this example, there arethree rows and four columns of cells. From a capacitor perspective,there are six rows of capacitors and eight columns of capacitors. Eachrow and each column of capacitors is coupled to a drive sense circuit(DSC). For example, each blue capacitor of a cell in a row of cells(e.g., C1, C5, C9, C13) is coupled to a blue outlined drive sensecircuit (DCS). The blue capacitors of the cells comprise rows 1, 3, and5.

As another example, each black capacitor of a cell in a row of cells(e.g., C4, C8, C12, C16) is coupled to a block outlined drive sensecircuit (DCS). The black capacitors of the cells comprise rows 2, 4, and6.

As yet another example, each red capacitor of a cell in a column ofcells (e.g., C2, C18, C34) is coupled to a red outlined drive sensecircuit (DCS). The red capacitors of the cells comprise columns 2, 4, 6,and 8.

As a further example, each green capacitor of a cell in a column ofcells (e.g., C3, C19, C35) is coupled to a green outlined drive sensecircuit (DCS). The green capacitors of the cells comprise columns 1, 3,5, and 7. In this example, there are forty-eight capacitors (c1-C48) andonly fourteen drive sense circuits.

In an example, the row 1 DSC circuit drives and senses the bluecapacitors in the first row of cells (C1, C5, C9, and C13). The bluecapacitors are coupled in parallel, thus their collective capacitancewith no compression is four times the minimum capacitance (assuming thecapacitors are similar). If one or more of the capacitors is compressed,the collective capacitance of row 1 changes and is detected by the row 1DSC. The row 1 DSC, however, cannot detect which of the four capacitorsis experience the compression.

The same applies for each of the other row DSCs. For instance, the row 2DSC drives and senses the collective capacitance of the black capacitorsC4, C8, C12, and C16; the row 3 DSC drives and senses the collectivecapacitance of the blue capacitors C17, C21, C25, and C29; the row 4 DSCdrives and senses the collective capacitance of the black capacitorsC20, C24, C28, and C32; the row 5 DSC drives and senses the collectivecapacitance of the blue capacitors C33, C37, C41, and C45; and the row 6DSC drives and senses the collective capacitance of the black capacitorsC36, C40, C44, and C48.

Continuing with the example, the column 1 DSC circuit drives and sensesthe green capacitors in the first column of cells (C3, C19, and C35).The green capacitors are coupled in parallel, thus their collectivecapacitance with no compression is three times the minimum capacitance(assuming the capacitors are similar). If one or more of the capacitorsis compressed, the collective capacitance of column 1 changes and isdetected by the column 1 DSC. The column 1 DSC, however, cannot detectwhich of the three capacitors is experience the compression.

The same applies for each of the other column DSCs. For instance, thecolumn 2 DSC drives and senses the collective capacitance of the redcapacitors C2, C18, and C34; the column 3 DSC drives and senses thecollective capacitance of the green capacitors C7, C23, and C39; thecolumn 4 DSC drives and senses the collective capacitance of the redcapacitors C6, C22, and C38; the column 5 DSC drives and senses thecollective capacitance of the green capacitors C11, C27, and C43; thecolumn 6 DSC drives and senses the collective capacitance of the redcapacitors C10, C26, and C42; the column 7 DSC drives and senses thecollective capacitance of the green capacitors C15, C31, and C47; andthe column 8 DSC drives and senses the collective capacitance of the redcapacitors C14, C30, and C46.

To identify a particular cell experiencing compression, capacitancechanges for at least one of its rows and at least one of its columns aredetected. For example, when row 1 DSC detects a capacitance change andcolumn 4 DSC circuit detects a capacitance change, then it is determinedthat the cell labeled TC2 is experience compression. In particular, bluecapacitor C5 and red capacitor C6 are being compressed. If row 1 andcolumn 4 are the only capacitor row and capacitor column to experience acapacitance change, then the row capacitance change is attributable tocapacitor C5 and the column capacitance change is attributable tocapacitor C6.

If, however, row 1 and column 4 are not the only capacitor row andcapacitor column to experience a capacitance change, then furtherprocessing is required to determine the capacitance change of eachcapacitor experiencing compression. FIGS. 26A-26D are schematic blockdiagrams of an example of such further processing.

FIG. 26A illustrates an applied force overlapping cells TC2, TC3, TC6,and TC7. The applied force has a magnitude gradient, where more force isrepresented by the color red and less force by the color yellow. In anexample, the shape of the applied force corresponds to the ball of footor a big toe.

FIG. 26B illustrates which of the drive sense circuits (DSC) detects acapacitance as a result of the applied force. In this example, acapacitance change is represented as “delta C” and no capacitance changeis represented as “no delta C”. As shown, rows 1-4 and column 3-6 areexperience a capacitance change and rows 5-8, columns 1, 2, 7, and 8 donot experience a capacitance change.

FIG. 26C illustrates the effected DSCs and capacitors of FIG. 26B. Inthis example, only capacitors C5 and C9 contribute to the capacitorchange of row 1; only capacitors C8 and C12 contribute to the capacitorchange of row 2; only capacitors C21 and C25 contribute to the capacitorchange of row 3; and only capacitors C24 and C28 contribute to thecapacitor change of row 4.

Also in this example, only capacitors C7 and C23 contribute to thecapacitor change of column 3; only capacitors C6 and C22 contribute tothe capacitor change of column 4; only capacitors C11 and C27 contributeto the capacitor change of column 5; and only capacitors C10 and C26contribute to the capacitor change of column 7. The next processing taskfor each effected row and column is to determine the amount of changefor each of the two effected capacitors. As an example, the nextprocessing task is to determine the capacitance change of each ofcapacitors C5 and C9 for row 1.

As part of the next processing step, the capacitance changes on the roware ranked from lowest to highest and the capacitance changes on thecolumns are ranked from lowest to highest. For this example, row 3 hasthe highest capacitance change, then row 2, then row 4, and row 1 hadthe lowest capacitance change. For the columns, column 5 had the highestcapacitance change, then column 4, then column 6, and column 3 had thelowest capacitance change.

FIG. 26D illustrates the row and column rankings for capacitive changes.The row and column rankings are used to establish a row-column intersectranking. In this example, the row ranking is multiplied by the columnranking to establish a row-column intersect score. The lower therow-column intersect score, the higher the capacitance change, whichequates to more applied force. In this example, the approximate centerof the applied force is at the intersection row 3 and column 5 since ithas the lowest row-column intersect score.

The row-column intersect scores are then processed to determine a cellscore. For example, the score for cell TC2 is the sum of the relevantrow-column scores, which are in red text in the table. The resultingscore is 36. The score for TC3 is 24, which is blue text; the score forTC6 is 24, which is green text, and the score for TC7 is 16, which is inblack text. The cell scores are used to determine a capacitance changeratio between the capacitances in an effected for and in an effectedcolumn.

For example, the capacitance change detected by a row DCS isΔC_total=A*ΔCi+B*ΔCj+C*ΔCk+D*ΔCl, with four capacitors in the row. Thecoefficients A, B, C, and D are determined based on the correspondingcell scores. As a specific example, row 4 includes capacitor C20 in cellTC5, capacitor C24 in cell TC6, capacitor C28 in cell TC7, and capacitorC32 in cell TC8. The cell scores for TC5 and TC8 are zero. Thus, for row4, the capacitance change equation is ΔC_total=0*ΔCi+B*ΔCj+C*ΔCk+0*ΔCl,which equals B*ΔCj+C*ΔCk.

The coefficients B and C are determined from the cell scores of TC6 andTC7. For instance, B=1−[TC6 score/(TC6 score+TC7 score) and coefficientC=1−[TC7 score/(TC6 score+TC7 score). Using the data of the table inFIG. 26D, B=1−(24/(24+16), which equals 0.4 and C=1−(16/(24+16), whichequals 0.6. Thus, 40% of the total capacitance change detected by therow 4 DSC is attributable to C24 and 60% of the total capacitance changeis attributable to C28. Similar functions are used to determine theindividual capacitance changes of the capacitors in cells TC2, TC3, TC6,and TC7. With the individual capacitances determined, the correspondingforce is calculable, then the reference plane, then the normal vector,and then the magnitude and direction of the applied impact force.

Note that the various calculations as discussed with reference to FIGS.17 through 26D are performed by the processing module of the forcedetection system 20 and/or by the computing entity. In an embodiment,the force detection system stores impedance values of the variablecapacitors per sampling interval. The computing entity functions toconvert the impedance into a capacitance value and the capacitance valueinto a pressure value (e.g., force over the area of a capacitor). Thecomputing entity then determines the reference plane and the normalvector.

FIGS. 27A-27C are schematic block diagrams of an example of determininga normal vector of a cell of a force detection system in response to animpact force. In this example, the cell includes a top layer capacitorC1, a compressible and/or flexible ground plane, and three lower layercapacitors C2 and C3. FIG. 27A illustrates a top view of the cell wherethe top layer capacitor C1 substantially overlaps the three lower-levelcapacitors. FIGS. 27B and 27C illustrate side views of the cell. In thisexample, the cell is coupled to four drive sense circuits (DSC), one toeach of the capacitors. The cell functions similarly to previouslydiscussed cells.

FIGS. 28A and 28B are schematic block diagrams of examples of placementof force cells within a sole of a shoe with respect to expected forcesapplied by a foot. FIG. 28A shows a full coverage cell placement patternwhere the cells are substantially evenly distributed throughout the solefrom a top view perspective. FIG. 28B shows the pressure sensor cellsarranged in a toe zone, a ball of foot zone, a later midfoot zone, and aheal zone, wherein, within one of the zones, the pressure sensor cellsare of approximately equal size. In another embodiment, the cells may beof different sizes. For example, a cell under the ball of foot is largerthan a cell under a toe. In another embodiment, less cells are used inthe selected coverage pattern.

FIG. 29 is a schematic block diagram of an example of an angular impactforce applied by a foot on the force detection system. In this example,a plurality of force cells is positioned from the medial side of a soleto the lateral side of the sole. As positioned, the cells are underneaththe toes (from a front of the shoe perspective) and able to detectforces as previously described.

FIG. 30 is a schematic block diagram of another example of an angularimpact force applied by a foot on the force detection system. In thisexample, the midsole has a U-shape, which causes the force to beradiated in a pattern has shown. This causes the ground reaction forceto be angled away from the body, which adversely affects athleticperformance. With the force detection system, such ground reaction forceinefficiencies can be detected.

FIG. 31 is a schematic block diagram of another example of cellplacement in a sole with respect to expected forces applied by a foot.In this example, nine cells are used and are of different sizes. Largercells are positioned in the ball of foot area and smaller cells arepositioned by the toes. The heal cells are smaller than the ball of footcells but larger than the toe cells.

FIGS. 32A-32C are schematic block diagrams of another embodiment offorce detection system 20. The force detection system 20 includes alayer of variable capacitors 200 and a circuitry section 104 in a soleof a shoe. The circuitry section 104 houses the circuitry of FIG. 3.

The layer of variable capacitors 200 includes variable capacitors thatcompress in the z-direction, variable capacitors that compress in they-direction, and/or variable capacitors that compress in thex-direction. The different compression orientated variable capacitorsmay be on the same layer or in different layers. In an embodiment, thedifferent compression orientated variable capacitors are in the samelayer.

FIGS. 33A-33E are schematic block diagrams of an example of a cell ofthe force detection system of FIGS. 32A-32C. FIG. 33A is a top view of aforce sensing cell that includes a z-direction compressible capacitor,y-direction compressible capacitors, x-direction compressiblecapacitors, and a cell housing. The cell may further include acompression plate.

The z-direction compressible capacitor changes its capacitance inaccordance with a force in the z direction, but negligibly changes itscapacitances as result of an x-direction force or a y-direction force.The y-direction compressible capacitor changes its capacitance inaccordance with a force in the y direction, but negligibly changes itscapacitances as result of an x-direction force or a z-direction force.The x-direction compressible capacitor changes its capacitance inaccordance with a force in the x direction, but negligibly changes itscapacitances as result of an z-direction force or a y-direction force.

Thus, when an applied impact force that includes x, y, and z componentsis applied to the cell, the z-direction compressible capacitor changesits capacitance based on the z component of the applied impact force;the y-direction compressible capacitor changes its capacitance based onthe y component of the applied impact force; and the x-directioncompressible capacitor changes its capacitance based on the x componentof the applied impact force. As such, the capacitance change of thez-direction compressible capacitor represents the z component of theimpact force; the capacitance change of the y-direction compressiblecapacitor represents they component of the impact force; and thecapacitance change of the x-direction compressible capacitor representsthe x component of the impact force.

From the x, y, and z force components determined based on capacitance,the magnitude and direction of the impact force on the cell can bedetermined. In essence, it is a conversion from Cartesian coordinates topolar coordinates.

FIG. 33B is a side view of an embodiment of the cell of FIG. 33A. Thecell includes the housing and the directional capacitors. In this sideview, which is from the x-z plane, the z-direction compressiblecapacitor is between the two x-direction compressible capacitors. Whenan impact force is applied to the cell that includes an x and a zcomponent, the z direction compressible capacitor changes itscapacitance based on the z direction force component. With a positive xforce component, the x-direction compressible capacitor in the positivex direction changes its capacitance based on the x direction forcecomponent. The x-direction compressible capacitor in the negative xdirection does not change its capacitance assuming that when no force isapplied, the capacitor is at its minimum (no compression) value.

In an embodiment, the x-direction compressible capacitors each havemid-point compression (e.g., 40% to 60% of full compression) when noimpact force is applied to the cell. In this manner, when an x force isapplied to the cell, one of the x-direction compressible capacitorscompresses further and increases its capacitance while the other iscompressed less and decreases its capacitance. The two changes are thenused to determine the x force magnitude and direction.

The y-direction compressible capacitors function in a similar manner asthe x-direction compressible capacitors, only in the y direction insteadof x direction.

FIG. 33C is a side view of an embodiment of the cell of FIG. 33A. Thecell includes the housing, the directional capacitors, and compressionplate. In this side view, which is from the y-z plane, the z-directioncompressible capacitor is below the compression plate, which is betweenthe two y-direction compressible capacitors. When an impact force isapplied to the cell that includes a y and a z component, the z directioncompressible capacitor changes its capacitance based on the z directionforce component. With a positive y force component, the y-directioncompressible capacitor in the positive y direction changes itscapacitance based on the y direction force component. The y-directioncompressible capacitor in the negative y direction does not change itscapacitance assuming that when no force is applied, the capacitor is atits minimum (no compression) value.

In an embodiment, the y-direction compressible capacitors each havemid-point compression (e.g., 40% to 60% of full compression) when noimpact force is applied to the cell. In this manner, when a y force isapplied to the cell, one of the y-direction compressible capacitorscompresses further and increases its capacitance while the other iscompressed less and decreases its capacitance. The two changes are thenused to determine the y force magnitude and direction.

FIG. 33D is a top view of a force sensing cell that includes az-direction compressible capacitor, x-direction compressible capacitors,and a cell housing. The cell may further include a compression plate.The compressible capacitors function as previously described. Such aforce sensing cell is used in the force detection system where there isa z force component and an x force component and a negligible y forcecomponent. For example, the cell is used for medial to lateral forcedetection in a shoe where there will be negligible toe to heal force.

FIG. 33E is a top view of a force sensing cell that includes az-direction compressible capacitor, y-direction compressible capacitors,and a cell housing. The cell may further include a compression plate.The compressible capacitors function as previously described. Such aforce sensing cell is used in the force detection system where there isa z force component and a y force component and a negligible x forcecomponent. For example, the cell is used for in the toe area.

FIG. 34 is a logic diagram of an example of a method for establishing afoot force sampling rate. The method begins at step 300 where aprocessing module of a foot force detection system determines anathletic mode. For example, an athletic mode is of whether an athlete isactively engaged in an athletic event or is not actively engaged in anathletic event. For example, a golfer playing golf is actively engagedand, if the golfer is in the club house, the golfer is not activelyengaged. As another example, a baseball player is actively engaged inplaying baseball when the player is on his/her feet and is not activelyengaged when seated (e.g., on the bench).

In an embodiment, the processing module detects an inactive to activefoot force pattern of a shoe, and/or a pair of shoes, that includes thefoot force detection system. For example, in golf, the processing moduledetects a foot pattern movement consistent with playing golf. As aspecific example, a foot pattern of walking the course and/or of drivinga golf cart. As another example, in baseball, the processing moduledetects a foot force pattern of being on the mound, in the batter's box,being on base, and/or being in the field.

The method branches at step 301 to step 302 when the athlete is activelyengaged and to step 304 when the athlete is not actively engaged. Atstep 302, the processing module determines whether the athlete is in aburst mode. For example, a burst mode for a golfer is when the golfer isabout ready to hit a golf ball through hitting the golf ball. As anotherexample, a burst mode of a baseball player is when the player is readyto hit a baseball, to throw a baseball, and/or is in the field readyinghimself or herself to catch a baseball.

In an embodiment, the processing module determines the athletic burstmode by detecting an active to burst foot force pattern of a shoe,and/or pair of shoes, that includes the foot force detection system.

When in the burst mode, the method continues at step 303 where theprocessing module sets a second sampling rate for the foot forcedetection system based on the athletic burst mode for sampling footforce data. The second mode sampling rate is set between 100 samples persecond to 10,000 or more samples per second depending on the athleticactivity. For example, detecting foot force of a sprinter requires ahigh sampling rate (e.g., greater than 1 KHz) to capture multiple framesof foot force data for each foot strike. The method repeats at step 302.

When in the active athletic mode but not in the athletic burst mode, themethod continues at step 305 where the processing module sets a firstsampling rate for the foot force detection system. The first samplingrate is less than the second sampling rate (e.g., the athletic burstsampling rate). For example, the first sampling rate is in the range of5% to 90% of the second sampling rate.

When not in the active mode, the method continues at step 304 where theprocessing module establishes an inactive sampling rate for the footforce detection system. The inactive sampling rate is set to a range of0% to 90% of the first sampling rate (e.g., active but not in burstmode).

In an embodiment, the processing module determines the sampling rate forthe foot force detection system further by determining a period of afoot to ground contact. The processing module then determines a dutycycle of the foot to ground contact for the period. The processingmodule then determines the sampling rate based on the duty cycle and theperiod. For example, the period of a foot to ground contact for asprinter (e.g., the inverse of time between left foot strikes and/or theinverse of time between right foot strikes) is about 2 Hertz (0.5seconds between left foot or right foot strikes, which assumes a 10second time in a 100-meter dash and a stride length (left foot to rightfoot) of 2.5 meters).

Continuing with the sprinter example, the duty cycle is the contact timeof the foot with ground. Assuming that the foot is in contact with theground for 40 milli-Seconds (mS), then the duty is 0.04/0.5, which is8%. If 100 foot-force samples are desired per foot strike, then a sampleneeds to be taken once every 40 mS/100, or once every 400 micro-Seconds(μS), which is a sampling rate of 2.5 KHz.

By varying the sampling rate during using of the foot force detectionsystem reduces power consumption, which is an important commercialaspect of the foot force detection system. Note that in a three-hourbaseball game or a football game, it is estimated that there is about 11minutes of actual play. By adjusting the sampling rate to be low, otherthan during the actual play, significant power is saved than having acommon sampling rate throughout a game.

FIG. 35 is a schematic block diagram of an example of a foot forcesampling rate. As shown, force for a foot is the y-axis and time is onthe x-axis. Time is broken down into a first inactive athletic modeinterface, an active athletic mode interval, and a second inactiveathletic mode interval. The active athletic mode interval includes anathletic burst period positioned in time between two active non-burstmode intervals.

During the inactive athletic modes, the sampling rate is set between 0and some low rate (e.g., 1-20 Hz). When the foot force detection systemdetects an inactive to active foot pattern, the active athletic modeinterval begins. In this mode, the sampling rate is set to a low tomedium sampling rate (e.g., 20 Hz to a few hundred Hz).

When an active to burst foot pattern is detection, the burst athleticmode interval begins. In this mode, the sampling rate is set to a mediumto high sampling rate (e.g., a few hundred Hz to 10 kHz or more). Whenthe system detects a burst to active foot pattern, the sampling rate isadjusted to the low to medium rate. When the system detects an active toinactive foot pattern, the sampling rate is adjusted to the 0 to lowrate.

FIG. 36 is a schematic block diagram of an example of a foot forcepattern for walking. In this example, force is switched from the leftfoot to the right foot with some force overlap in time.

FIG. 37 is a schematic block diagram of another example of a foot forcepattern running. In this example, there are periods of time whereneither foot is on the ground and short bursts of time when a foot is onthe ground. In running, the foot force can be up to six times bodyweight.

FIG. 38 is a schematic block diagram of another example of a foot forcepattern for hitting a golf ball or a baseball. Prior to hitting, weightis about equally distributed between the feet. During the backswing,more weight is transferred to the back leg and less is on the frontfoot. During the downswing, weight is being transferred from the backleg to the front leg. From the right foot to the left foot for aright-handed hitter.

At the point of contact, most of the weight is transferred to the frontleg (e.g., the left foot for a righty). As the hitter follows through,the weight eventually balances back out to being equally distributedbetween both feet.

A combination of foot force patterns can be used to detect an inactiveto active pattern, to detect an active to burst pattern, to detection aburst to active pattern, and an active to inactive pattern. For example,for a golfer, an inactive period would be detected when there is notpressure on either foot (e.g., sitting in a cart). The walking patternof FIG. 36 is used to detect an inactive to active pattern (e.g., golferis out of the cart and walking towards a golf ball).

When the golfer's feet settle to set up for a swing, the pattern of FIG.38 is used to detect the active to burst pattern and the burst to activepattern. When the golfer stops walking and there is not force on eitherfoot indicates the active to inactive pattern.

The patterns used to trigger the different sampling rates can beimplemented in a variety of ways. For example, the pattern for a golferis generic and includes a pattern as discussed above. As anotherexample, the pattern for a golfer is unique to the golfer based onhistorical foot force data. As yet another example, the pattern for asport is generic to the typical foot patterns of that sport. As afurther example, the pattern for an athlete for a specific sport isunique to the athlete based on historical foot force data.

FIG. 39 is a schematic block diagram of an embodiment of a foot forcedetection system 20-1 that includes a first shoe force detection unit320 and a second shoe force detection unit 321 that communication sensedsignals via the body 326 of a user of the system 20-1. Each of thedetection units 320 and 321 includes a plurality of variable capacitors,a plurality of drive sense circuits (DSC), a processing module 322, 323,and a communication unit 324, 325.

The variable capacitors vary their capacitance based on pressure. Inaddition, the variable capacitors have an electrically conductive plateto which the body, via the feet, is connected. One or more of the drivesense circuits (DSC) is operable to provide a drive signal to itscorresponding variable capacitor and, on the same line, sense one ormore sense signals of one or more variable capacitors. Other DSCs areoperable to provide a drive signal to their corresponding variablecapacitors.

In this example, DSC 2-1 of the second shoe force detection unit 321 isoperable to provide a drive signal to its variable capacitor and toreceive sense signals from its variable capacitor and from the variablecapacitors associated with DSC 1-1,1-2, and 2-2. DSC 1-1 provides afirst drive signal to its variable capacitor; DSC 1-2 provides a seconddrive signal to its variable capacitor; DSC 2-1 provides a third drivesignal to its variable capacitor; and DSC 1-1 provides a fourth drivesignal to its variable capacitor.

DSC 2-1 is further operable to receive a sense signal regarding itsvariable capacitor and sense signals regarding the other variablecapacitors via the body of the wearer of the foot force detectionsystem. A first sense signal corresponds to the first drive signalsupplied to the variable capacitor associated with DSC 1-1; a secondsense signal corresponds to the second drive signal supplied to thevariable capacitor associated with DSC 1-2; a third sense signalcorresponds to the third drive signal supplied to the variable capacitorassociated with DSC 2-1; and a fourth sense signal corresponds to thefourth drive signal supplied to the variable capacitor associated withDSC 2-2.

DSC 2-1 supplies the third drive signal to its variable capacitor andgenerates the third sensed signal based on a characteristic of itsvariable capacitor. For example, DSC 2-1 generates the third sensedsignal regarding an impedance of its variable capacitor. DSC 2-1converts the third sense signal into a third digital signal. It does thesame for the first, second, and fourth senses to produce first, second,and fourth digital signals.

In this example, processing module 323 and communication unit 325 areactive, while processing module 322 and communication unit 324 areinactive. With one set of processing module and communication unitactive at a time, overall power consumption of the foot force detectionsystem 20-1 is reduced.

Processing module 323 generates a first digital impedance for the firstvariable capacitor based on the first digital signal; generates a seconddigital impedance for the second variable capacitor based on the seconddigital signal; generates a third digital impedance for the thirdvariable capacitor based on the third digital signal; and generates afourth digital impedance for the fourth variable capacitor based on thefourth digital signal. The digital impedances may be stored in memoryand/or communicated to a computing entity via the communication unit325.

FIG. 40 is a schematic block diagram of another embodiment of a footforce detection system 20-1, which is similar to the system of FIG. 39.In this embodiment, DSC 1-2 is active to drive and sense signals and theother DSC are supplying drive signals. Further, processing module 322and communication unit 324 are active and processing module 323 andcommunication unit 325 are inactive.

DSC 1-2 functions similarly to DSC 2-1 as described with reference toFIG. 39 to produce the first, second, third, and fourth digital signals.Processing module 322 processes the first-fourth digital signals toproduce first-fourth digital impedances similarly to the processingperformed by processing module 323 as discussed with reference to FIG.39.

By switching back and forth between the first and second shoe forcedetection units being operable to process sensed signals and createdigital impedance values therefrom, overall power consumption of thefoot force detection system 20-1 is reduced. Further, the switching backand forth balances power consumption between the two shoe forcedetection units 320 and 321.

FIG. 41 is a schematic block diagram of an example of processing footforce detection. In this example, the drive sense circuits (DSCs) ofFIGS. 39 and 40 generate their respective drive signals using differentfrequencies. For example, DSC 1-1 generates a drive signal having anoscillating component at a first frequency (f1); DSC 1-2 generates adrive signal having an oscillating component at a second frequency (f2);DSC 2-1 generates a drive signal having an oscillating component at athird frequency (f3); and DSC 2-2 generates a drive signal having anoscillating component at a fourth frequency (f4).

In the example of FIG. 39, DSC 2-1 receives the sensed signals fromitself and the other DSCs. In this example, the received signal has fourfrequency components f1-f4. The processing module is configured orincludes, four bandpass filters (BPF 1-4), and four impedancecalculation units (z=v/i 1-4). The BPFs separate the frequencycomponents to produce the first, second, third, and fourth digitalvalues.

For the first digital value, the first impedance calculation unitgenerates a first impedance therefrom. For example, the first digitalvalue represents the current at the first frequency that is sourced tothe first variable capacitor (i.e., the output of the op amp of the DSCcorresponds to the current). The voltage supplied to the first variablecapacitor is fixed based on the reference signal. Thus, for the firstvariable capacitor at the first frequency, voltage and current areknown. As such, the first impedance value is equal to the voltagedivided by the current. The other impedance values are calculated in asimilar manner. Note that an impedance value is generated per intervalof a sampling rate of the foot force detection system.

FIG. 42 is a schematic block diagram of another example of processingfoot force detection. In this example, DSC 2-2 and 1-2 are shown, whichcorresponds to variable capacitors 2 and 4 and frequencies f2 and f4 ofthe example of FIG. 40. The processing module 322, 323 is shown toinclude BPF 2 and 4 and impedance calculators 2 and 4.

Each of the DSCs are shown with just the op-amp 330, 331 and thedependent current source 332, 333. Capacitor C_₂₋₂ represents thevariable capacitor associated with DSC 2-2 and capacitor C_₁₋₂corresponds to the variable capacitor associated with DSC 1-2. CapacitorC__(body) is the capacitance of the body, which is typically about 100pF. In this example, capacitance of capacitors C_₁₋₂ and C_₂₋₂ rangefrom 2.25 to 4.45 pF.

Each DSC functions to keep its input voltages of their respectiveop-amps equal. To do this, the output of the op amp is adjusted toadjust the current supplied by the respective dependent current source332, 333. As the load increases in impedance of a DSC, the current itproduces correspondingly increases, but the voltage at the inputs of theop amp remain constant. As such, DSC 2-2 keeps both inputs of its op ampequal to the reference voltage that has an oscillating component atfrequency f4 by regulating current i4. Similarly, DSC 1-2 keeps bothinputs of its op amp equal to the reference voltage that has anoscillating component at frequency f2 by regulating current i1.

As shown, i4=i6+i5−i2; i1=i3+i2−i5; Z_(C_2-2)=V_(C_2-2)/i6; andZ_(C_1-2)=V_(C_1-2)/i3. Thus, to determine the impedance of the variablecapacitors (Z_(C_2-2) and Z_(C_1-2)), i3 and i6 need to be independentlydetermined. Due to the coupling of the body capacitance, determining i3and i6 include a current component from both DSCs. FIGS. 43 and 44illustrate an example of determining i3 and i6.

FIG. 43 is a schematic block diagram of another example of processingfoot force detection. In this example, the reference signal received byop amp 330 of DSC 2-2 is a voltage reference signal that includes a DCcomponent and an oscillating component that has a frequency at f4 (e.g.,10 KHz or more). The reference signal received by the op amp 331 of DSC1-2 is a current reference signal that has a DC component. As such, i1is equal to the reference current signal and V2 will vary based on loadvariance.

In the AC domain, i4=i6+i5; i1=i3−i5; i1=Iref=0. What is also known:V1=Vref @f4; V_(C_body)=V1−V2; the body capacitance is known (e.g., 100pF). The impedance of the body capacitor is calculated asZ_(C_body)=1/(2*π*f4*C__(body)) and current i5 is calculated as(V1−V2)/Z_(C_body). Further, i3=Iref+i5, which in the AC domain, i3=i5.The impedance of Z_(C_1-2) is equal to V2/i3. From the preceding, thecapacitance of C_₁₋₂ is calculated as 1/(2*7π*f4*Z_(C_1-2)).

FIG. 44 is a graphic diagram of an example of signals of the example ofFIG. 43. In this example, i4 lags V1 by 90 degrees since it is driving aprimarily capacitor load (e.g., C_₂₋₂ in parallel with the seriescombination of C__(body) and C_₁₋₂). With i1=Iref, then V2 is 180degrees out of phase of V1 and its magnitude is scaled based on thecapacitance ratio of C__(body) to C_₁₋₂. V_(C_body) is equal to V1−V2and i5=V_(C_body)/Z_(C_body).

FIG. 45 is a schematic block diagram of another example of processingfoot force detection. In this example, the reference signal received byop amp 331 of DSC 1-2 is a voltage reference signal that includes a DCcomponent and an oscillating component that has a frequency at f4 (e.g.,10 KHz or more). The reference signal received by the op amp 330 of DSC2-2 is a current reference signal that has a DC component. As such, i4is equal to the reference current signal and V1 will vary based on loadvariance.

In the ΔC domain, i1=i2+i3; i4=i6−i2; i4=Iref=0 (at AC). What is alsoknown: V2=Vref @f4; V_(C_body)=V2−V1; the body capacitance is known(e.g., 100 pF), the impedance of the body capacitor is known, and theimpedance of C_₁₋₂ is known. Current i3 is calculated as (V2)/Z_(C_1-2).Further, i6=i2=i1−i3. Since i1 is known based on the output of op amp331 and i3 was just calculated, i6 is known. Further, V1 is known forthe output of op amp 330. As such, the impedance of Z_(C_2-2) isdetermined based on V1/i6. From the preceding, the capacitance of C_₂₋₂is calculated as 1/(2*π*f4*Z_(C_2-2)).

FIG. 46 is a graphic diagram of an example of signals of the example ofFIG. 45. In this example, i1 lags V2 by 90 degrees since it is driving aprimarily capacitor load (e.g., C_₁₋₂ in parallel with the seriescombination of C__(body) and C_₂₋₂). With i4=Iref, then V1 is 180degrees out of phase of V2 and its magnitude is scaled based on thecapacitance ratio of C__(body) to C_₂₋₂. V_(C_body) is equal to V2−V1and i2=i6=V_(C_body)/Z_(C_body).

FIG. 47 is a schematic block diagram of an example of sampling periodfor foot force detection. In this example, two cycles of sampling areshown: sample cycle i and sample cycle i+1. Each sample cycle includes aplurality of time intervals. Four in this example.

For an interval of a sample cycle, a drive sense circuit (DSC) isenabled to provide a drive signal to its corresponding variablecapacitor. In this manner, the same frequency can be used for theoscillating component of the reference signals for each of a pluralityof DSCs.

FIG. 48 is a schematic block diagram of another example of processingfoot force detection. In this example, DSC 1-1 is enabled in interval 1of a four-interval sample cycle to provide a drive signal to itscorresponding variable capacitor. The drive signal includes anoscillating component at frequency f1 (e.g., 10 KHz or higher). A firstsensed signal is coupled through the body to DSC 2-1, which creates adigital signal therefrom. The BPF filters the digital signal to producea digital value and the impedance calculator generates a digitalimpedance value for the first variable capacitor (VC 1-1).

The process is repeated for the second variable capacitor (VC 1-2)during the second time interval and for the fourth variable capacitor(VC 2-2) during the fourth interval. During the third interval, DSC 2-1creates the sense signal directly from the third variable capacitor (VC2-1). The sensed signal is converted into a digital signal andsubsequently converted into a digital impedance value for the thirdvariable capacitor. Such processing occurs during the sample cycles.

FIG. 49 is a schematic block diagram of an embodiment of an athletemonitoring system 340. The system 340 includes a localized radar system342, foot force detection system 341, and a processing module 343. Thefoot force detection system 341 includes a left foot force detectionunit 344 and a right foot force detection unit 345. The foot forcesystem 341, the first foot force detection unit 344, and/or the rightfoot force detection unit 345 may be implemented as previously discussedand/or subsequently discussed. Note that the system may be implementedand/or installed in a pair of shoes.

The system 340 also includes a plurality of body position beacons 346.When the system is in use, the body position beacons 346 are positionedon the body at various locations to track movement of the body. Thelocalized radar system 342 creates a localized radar coordinate system347, as shown in FIG. 50, in which the athlete is positioned. As shownin FIG. 50, the body position beacons are located on the body from headto toe and front to back. The number and location of beacons 346 dependson the athlete, the skill level of the athlete, the sport in which theathlete is participating, and/or a desired bio-mechanical functions ofthe athlete to be studied.

The localized radar system 342 samples positioning of the beacons withreference to the localized radar coordinate system 347 at a samplingrate to produce frames of body position data. The sampling rate dependson the anticipated speed of the body part movement and the desiredgranularity of movement data. For example, a pitcher's hand is moving at100 miles per hour and, if a desired movement granularity is 5millimeters, then the sampling rate needs to be 8,940 per second. Assupport, 100 mph=44,704 mm/sec; divide that by 5 mm yields 8,940intervals/second.

Body parts that will not be moving as fast, for example, the core, canhave a slower sampling rate. For example, if the maximum speed of thecore is 10 mph and 5 mm movement resolution is desired, then thesampling rate would be 894 cycles per second.

The foot force detection system 341 generates, at its own sampling rate,a plurality of frames of left foot force data and a plurality of framesof right foot force data. The processing module 343 (which may be aseparate processing module and/or a processing module of the localizedradar system 342 and/or of the foot force detection system 341)correlates the frame of body position data with the frames left andright foot force data to produce an integrated ground-body interactiondata and athletic movement data.

The system 340 is capable of providing in game and/or in practiceathletic movement data and foot force data. It is the first athleticperformance system to integrate both data types. It is also the first toprovide in game and/or in practice accurate athlete movement data.Current movement data monitoring systems (e.g., bat speed, arm speed,digital pedometers, and the like), use estimates and can be as much as30% off in their estimates. The present system 340 can provide up to 5mm movement resolution at a sampling rate of 10 KHz, with millimeters ofaccuracy.

In an embodiment, the processing module correlates the data by timealigning a frame of the body position data, a frame of the left footforce data, and a frame of the right foot force data to produce framecorrelated data. The processing module then determines, based on severalframe correlated data, force vector motion data from the ground, throughthe shoes, and into the body. The processing module generates theintegrated ground-body interaction data and athletic movement data basedon the force vector motion data.

FIG. 51 is a schematic block diagram of an example of athlete monitoringby the localized radar system 342. The radar system 342 includes atleast three receivers (3 shown, 352-354) located at different positionswithin the localized radar coordinate system and at least onetransmitter (1 shown, 350) located at a different position within thelocalized radar coordinate system. During a cycle of the sampling rate,the transmitter 350 transmits a beacon signal 351 that is targeting afirst RF device 346-1 (e.g., a first body position beacon such as anRFID tag or the like). The targeting may be done in a variety of ways.For example, the targeting is done using a frequency divisionmultiplexing concept where each RF device is allocated, and tuned to, aunique frequency. As another example, the targeting is done using a timedivision multiplexing concept where, in a cycle of the sampling rate,the RF devices are allocated a time interval. In yet another example, acombination of time and frequency division multiplexing is used.

When the RF device 346-1 receives the beacon signal 351, it generates aring-back signal 355 therefrom. In an embodiment, the RF device usesback scattering to create and transmit the ring-back signal 355. Each ofthe receivers 352-354 receive the ring-back signal.

The transmission of the beacon signal 351 and the reception of thering-back signal 355 by each of the receivers are time-stamped. Theprocessing module 343 processes the timing of signals to determine arelative position of the RF device to the receivers. For example, thereceivers are located at known locations with respect to each other(e.g., are at known or determinable locations in the localizedcoordinate system).

The processing module calculates the distance between each receiver andthe RF device based on the timestamps and a known processing time of theRF device to create the ring-back signal from the beacon signal. Theprocessing module then triangulates the position of the RF device withrespect to the receivers based on the distances to produce a relativeposition 356 of the RF device.

The processing module then maps the relative position 356 of the RFdevice to the localized coordinate system to produce a mapped location357. Thus, on a sample-by-sample basis, the motion of the RF device isdetermined within the localized coordinate system.

FIG. 52 is a schematic block diagram of an example of athlete relativepositioning. In this example, the three receivers 353-354 are positionedwithin the localized radar coordinate system 347 at (x1, y1, z1), (x2,y2, z2), and (x3, y3, z3), respectively. The relative position 356 ofthe RF device 346-1 is based on the distances d1-d3 between the RFdevice and the receivers and the location of the receivers.

In an embodiment, the processing module determines the relative position356 by, for a first receiver 353, a first time offset between the firstbeacon signal and the ring-back signal received by the first receiver toproduce a first round-trip time. For example, the processing modulesubtracts the timestamp of the beacon signal from the timestamp of thereceived ring-back signal to produce a total time. The processing modulethen subtracts the processing time of the RF device to produce thering-back signal from the total time to produce the first round-triptime. The processing module does similar processing for the second andthird receivers.

The processing module then calculates a first distance between the firstRF device and the first receiver based on the first round-trip time. Forexample, an RF signal travels at the speed of light (c), which is 3×10⁸m/second. Thus, the distance between the RF device and the firstreceiver is c*(first round-trip time)*0.5. The processing modulecalculates the distance between the RF device and the other tworeceivers in a similar manner. From the distances, the processing modulecalculates the relative position of the RF device 346-1.

FIG. 53 is a schematic block diagram of an example of athlete coordinatesystem positioning, which builds on the example of FIG. 52. The relativeposition of the RF device 346-1 is mapped to the coordinate system 347.For this sample of the position of the RF device, it is located at (x4,y4, z4).

FIG. 54 is a schematic block diagram of an example of determiningathlete relative positioning. In an embodiment, the beacon signalincludes a repetitive pattern (e.g., a square wave, a sinusoid, atriangle wave, etc.) at a given frequency. In this instance, thering-back signal is a delayed representation of the repetitive pattern.The processing module determines the time offset between the beaconsignal and the ring back signal over a plurality of cycles of therepetitive pattern. In an example, the processing module determines anoffset for each cycle and processes the plurality of offsets (e.g.,averages them, finds a mean, etc.) to produce the time offset. Inanother example, the processing module determines the time offset basedon the start of the beacon signal and the end of the ring-back signal,subtracting out processing times, and factoring the number of cycles.

FIG. 55 is a schematic block diagram of another example of determiningathlete relative positioning. In this example, the attenuation of an RFsignal is plotted over distance. The greater the distance, the greaterthe attenuation. In air, the attenuation of an RF signal is calculatableas Pr/Pt=(c/4*f*π*d){circumflex over ( )}2. Thus,d=(c/4*π*f)(Pt/Pr){circumflex over ( )}½; where Pr is the power of thereceived RF signal, Pt is the power of the transmitted signal, c is thespeed of light, f is the frequency of the RF signal, and d is thedistance between the receiver and transmitter.

FIG. 56 is a schematic block diagram of another example of determiningathlete relative positioning that uses the graph of FIG. 55. In thisexample, the local radar system includes at least threetransmitter/receiver units (Tx/Rx). Each Tx/Rx unit transmits an RFsignal at a known power level (e.g., Pt is known). The RF device 346-1includes a power detection module that determines the received strengthof the RF signal (e.g., Pr is determined). The RF device transmits thereceived signal strength back to the appropriate Tx/Rx unit.

The processing module calculates the distance between each of the Tx/Rxunits and the RF device based on the curve of FIG. 55 and thecorresponding equations. For example, if the frequency is 60 GHz, thetransmit power is 100 μWatts and the received power is 15.85 pWatts,then the distance is about 1.00 meters. For a 4 mm resolution (e.g.,d=1.004 meters), the received power changes to 15.72 pWatts.

As another example, at a frequency of 600 MHz, and a transmit power of10 μWatts, the received power 1.00 meters away is 15.85 nWatts. For a 4mm resolution (e.g., d=1.004 meters), the received power changes to15.72 nWatts. Once the distances between the Tx/Rx units and the RFdevice are calculated, the relative position of the RF device isdetermined as previously discussed.

FIG. 57 is a logic diagram of an example of method for determiningathlete positioning. The method begins at step 360 where the processingmodule determines, for a first receiver, a first power differencebetween a first component of the first beacon signal and the ring-backsignal received by the first receiver. The method continues at step 361where the processing module determines, for a second receiver, a secondpower difference between a second component of the first beacon signaland the ring-back signal received by the second receiver.

The method continues at step 362 where the processing module determines,for a third receiver, a third power difference between a third componentof the first beacon signal and the ring-back signal received by thethird receiver. In an embodiment, the first component is a firstsinusoidal signal having a first frequency, the second component is asecond sinusoidal signal having a second frequency, and the thirdcomponent is a third sinusoidal signal having a third frequency.

The method continues at step 363 where the processing module calculatesa first distance between the first RF device and the first receiverbased on the first power difference and a path loss function (e.g., thecurve of FIG. 55 and the corresponding equations). The method continuesat step 364 where the processing module calculates a second distancebetween the first RF device and the second receiver based on the secondpower difference and the path loss function.

The method continues at step 365 where the processing module calculatesa third distance between the first RF device and the third receiverbased on the third power difference and the path loss function. Themethod continues at step 366 where the processing module calculates therelative position based on the first, second, and third distances.

FIG. 58 is a schematic block diagram of another example of athletepositioning. In this example, the origin of the localized radarcoordinate system 347 is associated with a particular point on theathlete's body (e.g., belly button, heel of left foot, heel of rightfoot, top of head, etc.). In a specific example, the z-axis of thelocalized radar coordinate system is perpendicular to the ground, apositive direction is away from the ground, and passing through theorigin; the x-axis of the localized radar coordinate system is parallelto the ground, has a positive direction to the front of the body, andpassing through the origin; and the y-axis of the localized radarcoordinate system is parallel to the ground, has a positive direction tothe right of the body, and passing through the origin.

FIG. 59 is a schematic block diagram of an embodiment of an athletemonitoring system 340-1, which includes the localized radar system 342and the processing module 343. The system further includes body positionbeacons placed on an athlete. The localized radar system creates alocalized radar coordinate system in which the athlete is positioned.The localized radar system further functions to, at a sampling rate,produce a plurality of frames of body position data based on determininglocation of the body position beacons within the localized radarcoordinate system. The processing module correlates the frames of bodyposition data to athletic movement data.

FIG. 60 is a schematic block diagram of another embodiment of foot forcedetection system 380. The system 380 includes variable capacitors 370,drive sense circuits (DSC), one or more processing modules 322, 323, anda power unit 371. The power unit 371 includes a battery 372 and a powerharvesting circuit 373, which individually, or collectively, producepower 375 that powers the system 380. The variable capacitors 370, theDSCs, and the processing module 322, 323 operate as previously discussedto produce digital impedance values for the capacitors 370, which variesbased on pressure. The power harvesting circuit 373 may be implementedin a variety of ways as shown in the examples of FIGS. 62-65.

FIG. 61 is a schematic block diagram of an embodiment of a power unit371 of a foot force detection system 380. The power unit 371 includestwo or more power harvesting circuits 373-1, -2, a power control circuit382, a power supply circuit 381, a battery charger 384, an electricstorage device 383 (optional), and the battery 372. The power supplycircuit 381 may be implemented in a variety of ways to generate one ormore DC voltages at current level to produce the power 375. For example,the power supply circuit is a linear regulator. As another example, thepower supply is a buck, boost, or fly-back power supply. Each of thepower harvesting circuits 373-1, -2 may be implemented in a variety ofways as shown in the examples of FIGS. 62-65.

The power control circuit 382 is a processing module, or portion of aprocessing module, that is programmed and/or configured to control thesources and/or distribution of power within the foot force detectionsystem 380. In a first mode, the power control circuit provideselectricity (e.g., voltage and current) of one or both of the powerharvesting circuits to the power supply circuit 381. The power supplycircuit 381 generates one or more DC voltages from the electricity. Inthis mode, the power harvesting circuit(s) is/are providing the powerfor the system 380.

In a second mode, the power control circuit 382 provides the electricityof one or more of the power harvesting circuits to the battery charger384 for charging the battery 372. In a third mode, the power controlcircuit 382 provides the electricity of one or more of the powerharvesting circuits to the electric storage device 383, which is acapacitor and/or an auxiliary battery coupled via the battery charger384.

The processing module 322, 323 of the foot force detection system 380determines which mode to use. Whenever a power harvesting circuit canproduce electricity (e.g., a voltage and/or a current), the processingmodule determines how best to use the electricity and/or how best toextend a battery charge. When the system 380 is in use and a powerharvesting circuit is producing electricity, the processing moduleenables the first mode such that the power harvesting circuit(s) is/areproviding the power 375 for the system and the battery 372 is supplyinglittle to no power. In an embodiment, the power harvesting circuitsgenerate a voltage that is greater than the battery voltage such that,when a power harvesting circuit is active, is supplies a majority of theelectricity (voltage and current) to the power supply circuit 381.

When a power harvesting circuit is producing electricity, the processingmodule determines the charge level of the battery. If battery charge isbelow a charge threshold (e.g., 75% charged), the processing moduleenables the second mode to provide electricity of a power harvestingcircuit to the battery charger 384 to charge the battery. If batterycharge at or above the charge threshold, the processing module enablesthe third mode to provide electricity of a power harvesting circuit toelectric storage device 383 for storing the electricity (e.g., storecharge by a capacitor or store voltage potential by a battery). When thesystem 380 is in use, the processing module can enable the second orthird mode in conjunction with the first mode.

FIG. 62 is a schematic block diagram of an example of a power harvestingcircuit 373 of a power unit 371. The power harvesting circuit 373includes a radio frequency (RF) power harvesting unit (e.g., 514 of FIG.100). The RF power harvesting circuit receives an RF signal via anantenna. The signal is a cell phone signal, an RFID signal, a WLAN, aBluetooth signal, a ZigBee signal and/or a non-standard RF signaltransmitted for the purpose of power harvesting. The RF power harvestingcircuit rectifies the RF signal, using a rectifier circuit (e.g., fullor half rectification), to produce a rectified signal. The RF powerharvesting circuit filters the rectified signal, using a filter circuit(e.g., a capacitor and/or inductor) to produce a DC voltage 393.

FIG. 63 is a schematic block diagram of another example of a powerharvesting circuit 373 of a power unit 371. The power harvesting circuit373 includes a thermoelectric generation unit, which converts heat intoelectrical power. The thermoelectric generation unit includes a firstthermoelectric conductive plate, a second thermoelectric conductiveplate, a third thermoelectric conductive plate, a first thermo dopedmaterial between the first and second thermoelectric conductive plates,and a second thermo doped material between the first and thirdthermoelectric conductive plates. The first and second doped materials(e.g., p-doped and n-doped semiconductors) are doped with differentSeebeck coefficients.

In this configuration, when heat (e.g., of the body) is applied to thefirst plate, the doped materials cause current 394 to flow in the secondand third plates, which are at a cooler temperature than the firstplate. For instance, current (J) equals −σSAT, where σ is the localconductivity, S is the Seebeck coefficient (thermopower), and ΔT is thetemperature gradient.

FIG. 64 is a schematic block diagram of another example of a powerharvesting circuit 373 of a power unit 371. The power harvesting circuit373 includes a piezoelectric plate 395 and a filtering circuit 396. Thepiezoelectric plate generates an AC signal when weight of a wearer of ashoe is applied to it. The filtering circuit 396 (e.g., a rectifier, acapacitor, and/or an inductor) converts the AC signal into a DC voltage393.

FIG. 65 is a schematic block diagram of another example of a powerharvesting circuit 373 of a power unit 371. The power harvesting circuit373 includes a photovoltaic cell 397 and a storage circuit 398. Thephotovoltaic cell 397 produces a current from light. The storage circuit398 stores the current (e.g., a capacitor storage current as a chargeand/or a battery that stores the current as a voltage potential) andproduces therefrom a DC voltage 399.

FIGS. 66A and 66B are side view diagrams of an embodiment of a left shoeand a right shoe; each of which includes a shoe sensor system 416-L(left) and 416-R (right). The shoes may be sports specific athleticshoes (e.g., baseball, basketball, golf, tennis, track & field, running,etc.), walking shoes, dress shoes, work boots, hiking shoes or boots,etc.

In an embodiment, the shoe sensor system is located on or within theinsole and/or midsole of the shoe and functions to capture a multitudeof information. For example, the shoe sensor system 16 gathers data of auser's movements (e.g., running, jumping, walking, hitting a golf ball,hitting a baseball, pitching a baseball, playing basketball, etc.) forsubsequent analysis (e.g., determine ground reaction forces, weightdistribution, stride length, time duration of activity, imbalances inweight distribution, imbalances in stride length, elevation ascended,distance traveled, elevation descended, foot rotation, form, gait,etc.). The data includes ground reaction forces from a plurality ofpressure sensing element and three-dimensional foot positioning datafrom one or more accelerometers and/or gyroscopes. In addition, the datais further analyzed to determine whether performance of a physicalactivity is being done optimally (e.g., with proper form, withconsistency, without undue stress on the body, level of fatigue, etc.).When the physical activity is being performed less than optimally, thecorrective measures are determined based on the cause, or causes, of theless than optimal performance.

With the shoe sensor system 416 within each shoe 412 and 414, the shoescan be used in game to collect in-game data. For example, the shoes arebaseball spikes worn by a pitcher. Each shoe gathers foot force datafrom the plurality of pressure sensing elements and gathersthree-dimensional (3D) foot data (e.g., x-y-z data from anaccelerometer). The foot force data and the 3D foot data are sent via awireless link (e.g., a Bluetooth link) to a computing device that is offthe field of play. The computing device processes the data to determineground reaction forces of various locations on each foot, weightdistribution, balance, stride length, etc., which can be used todetermine the pitcher's level of fatigue, efficiency, etc.

FIGS. 66C and 66D are side view diagrams of another embodiment of a leftshoe and a right shoe; each of which includes a dongle 415, pressuresensing elements 420, and one or more accelerometers 422. The dongle 415includes a control circuit that communicates with the pressure sensingelements 420 and the accelerometer(s) 422 and also wirelesslycommunications the collected data to a computing device. The dongle 415is a relatively small device (e.g., less than 1 inch×1 inch×½ inch) thatincludes an exterior housing for containing a control circuit board. Thedongle 415 may be clipped to the heel or lateral side of the shoe asshown in FIG. 66C or clipped or laced into the laces of the shoe asshown in FIG. 66D. Note that the dongle 415 may be attached to otherlocations on each shoe and in different locations from shoe to shoe.Further note that communication between the dongle 415 and the pressuresensors in the shoes may be done via the body.

FIG. 67 is a schematic block diagram of an embodiment of a wirelessin-shoe physical activity monitoring apparatus 417 and a computingdevice 425. The wireless in-shoe physical activity monitoring apparatus417 includes a right shoe sensor system 416-R and a left shoe sensorsystem 416-L. As will be described in greater detail with reference toFIG. 70 and other figures, each shoe sensor system 416 includes pressuresensor elements 420-1 through 420-x, an accelerometer 422, and controlcircuit 424. The control circuit 424 includes a power source circuit424, a clock circuit 428, a processing module 430, memory 432, awireless communication transceiver 434, and a sampling signal generator435. The processing module 430 and the wireless communicationtransceiver 434 are shown in this Figure.

The computing device 425 is any electronic device that can communicatedata, process data, and/or store data. As an example, the computingdevice 425 is a portable computing device and/or a fixed computingdevice. A portable computing device may be a social networking device, agaming device, a cell phone, a smart phone, a personal digitalassistant, a digital music player, a digital video player, a laptopcomputer, a handheld computer, a tablet, a video game controller, and/orany other portable device that includes a computing core. A fixedcomputing device may be a personal computer (PC), a computer server, acable set-top box, a satellite receiver, a television set, a printer, afax machine, home entertainment equipment, a video game console, and/orany type of home or office computing equipment that includes a computingcore.

The computing device 425 includes a computing core, user interfaces 33,network interface(s) 435, a wireless communication transceiver 429, andmemory device(s) 437. The user interfaces 433 includes one or more inputdevices (e.g., keypad, keyboard, touchscreen, voice to text, etc.), oneor more audio output devices (e.g., speaker(s), headphone jack, etc.),and/or one or more visual output devices (e.g., video graphics display,touchscreen, etc.). The network interface(s) 435 includes one or morenetworking devices (e.g., a wireless local area network (WLAN) device, awired LAN device, a wireless wide area network (WWAN) device (e.g., acellular telephone transceiver, a wireless data network transceiver,etc.), and/or a wired WAN device). The memory device(s) 437 includes oneor more flash memory devices, one or more hard drives, one or more solidstate (SS) memory devices, and/or cloud memory.

The computing core includes a processing module 427 and other computingcore components 431. The other computing core components include a videographics processing unit 60, a memory controller, main memory (e.g.,RAM), one or more input/output (I/O) device interface module, aninput/output (I/O) interface, an input/output (I/O) controller, aperipheral interface, one or more USB interface modules, one or morenetwork interface modules, one or more memory interface modules, and/orone or more peripheral device interface modules. Each of the interfacemodules includes a combination of hardware (e.g., connectors, wiring,etc.) and operational instructions stored on memory (e.g., driversoftware) that is executed by the processing module and/or a processingcircuit within the interface module. Each of the interface modulescouples to one or more components of the computing device 425. Forexample, one of the IO device interface modules couples to an audiooutput device. As another example, one of the memory interface modulescouples to flash memory and another one of the memory interface modulescouples to cloud memory (e.g., an on-line storage system and/or on-linebackup system).

The wireless communication transceiver 429 of the computing device 425and the wireless communication transceivers 434 of the shoe sensorsystems 416 are of a like transceiver type (e.g., Bluetooth, WLAN,ZigBee, etc.). The transceivers 434 communicate directly withtransceiver 429 to share gathered data by the respective shoe sensorsystems 416 and/or to receiving instructions from the computing device425. In addition to or in the alternative, the transceivers 434communicate gathered data between them and one of the transceivers 434communicates the collective data to the transceiver 429.

The computing device 425 processes the data to produce a variety ofresultants. For example, the computing devices processes data from theshoe sensor systems 416 to determine a distance traveled during a timeperiod, which may be an entire time duration of a physical activity,time intervals (e.g., 5-minute intervals, etc. As another example, thecomputing devices processes data from the shoe sensor systems 416 todetermine stride length data (e.g., maximum stride length, minimumstride length, average stride length, stride length for a time interval,stride length of a distance segment, etc.).

As another example, the computing devices processes data from the shoesensor systems 416 to determine a time duration of the physical activity(e.g., walking, running, playing a sport, executing an athleticmovement, lifting weights, cross-fit training, etc.). As anotherexample, the computing devices processes data from the shoe sensorsystems 416 to determine a fatigue indication (e.g., shortening ofstride, pace slowing, change in foot forces, etc.). As another example,the computing devices processes data from the shoe sensor systems 416 todetermine injury prevention indicators (e.g., recognize change in data,where change is likely caused by fatigue, cramping, muscle strain,etc.).

As another example, the computing devices processes data from the shoesensor systems 416 to determine elevation tracking for the time period(e.g., steps climbed, elevation changes in a run, a walk, or a hike,etc.). As another example, the computing devices processes data from theshoe sensor systems 416 to determine running optimization (e.g., properfoot positioning & weight distribution when running, balanced strides,stride length training, increase ground reaction force, reduce foot toground contact time, etc.). As another example, the computing devicesprocesses data from the shoe sensor systems 416 to determine rotationalsport optimization (e.g., weight distribution, ground reaction forces,balance, linear movement, rotational movement, etc.).

The computing device 425 further includes operational instructions togenerate a graphical user interface for the recording, gathering, and/orprocessing of the data of the shoe sensor systems 416. For example, thegraphical user interface (GUI) displays information regarding theprocessing of the data. As a specific example, the GUI displaysinformation about a run, such as time duration, stride lengthinformation, foot force information, gait information, etc. As anotherexample, the GUI displays, in real time, foot forces and footpositioning during a physical activity to determine one or more ofproper form, fatigue analysis, injury predictive analysis, weightdistribution, and corrective measures of form.

In another embodiment, the foot force detection system includes firstand second shoe force detection units (e.g., left shoe and right shoesystems 416 L & R). Each shoe force detection unit includes a pluralityof pressure sensors, a processing module, and a communication unit. Thepressure sensors, when active, produce force data. The processingmodule, when active, produces a digital representation of the forcedata. The communication unit of one of the shoe force detection units,when active, communicates foot force data with the communication unit ofthe other shoe force detection unit.

In an embodiment, the first communication unit includes a first shoearea network transceiver (e.g., a low power high frequency transceiverthat is standard compliant or proprietary). The second communicationunit includes a second shoe area network transceiver (e.g., a low powerhigh frequency transceiver that is standard compliant or proprietary).In this embodiment, the foot force data is communicated via the firstand second shoe area network transceivers. To communicate data to thecomputing entity, the first and/or second communication units includeanother transceiver that is compatible to a transceiver of the computingentity. In another embodiment, the first and second communication unitscommunicate using light transceivers (e.g., IrDA complianttransceivers).

FIG. 68 is a schematic block diagram of an example of communication viathe body. In this example, each communication unit includes a drivesense circuit (DSC) 22 and a digital filter 402, 403. Each DSC 22includes an op amp 30, an ADC 35, a feedback circuit 31, and a dependentcurrent source 32.

For data to be communicated from DSC 22-1 to DCS 22-2 via the body, DSC22-1 receives first transmit data that includes an oscillating componentat a first frequency (f1). The data is modulated on the oscillatingcomponent using amplitude shift keying, phase shift keying, and/oramplitude modulation. Through the dependent current source, the firsttransmit signal at f1 is communicated through the body to DSC 22-2.Similarly, second transmit data (which has an oscillating component atf2) is transmitted from DSC 22-2 to DSC 22-1 via the body.

The op amp 30 of DSC 22-1 receives the second transmit signal at f2 viathe body. Through the closed loop feedback, the second transmit signalat f2 is regulated out as an error signal. The error signal produced bythe op amp, which includes a representation of the transmit signal atf2, is converted into a digital signal by the ADC 35. The digital filter402 bandpass filters the digital signal to recover the second transmitsignal at f2 as a received signal at f2.

FIG. 69 is a schematic block diagram of an example of communication viathe body. This example is similar to the example of FIG. 68 with theaddition of variable capacitors 21-1. In this example, DSC 22-1 and DSC22-2 communicate with each other as described with reference to FIG. 68.In this example, DSC 22-1 senses its variable capacitor using areference signal that has an oscillating component at f3 and DSC 22-2senses its variable capacitor using a reference signal that has anoscillating component at f4 as previously discussed with at leastreference to FIG. 4A.

FIG. 70 is a schematic block diagram of an embodiment of a shoe sensorsystem 416 that includes pressure sensor elements 420-1 through 420-x,an accelerometer 422, and control circuit 424. The control circuit 424includes a power source circuit 426, a clock circuit 428, a processingmodule 430, memory 432, a wireless communication transceiver 434, and asampling signal generator 435. The pressure sensing elements 420includes one more of a resistive pressure sensor, a piezoelectricpressure sensor, a capacitive pressure sensor, and an inductive pressuresensor and are distributed in a pattern having a shape corresponding toan outline a human foot as will be discussed with reference to one ormore subsequent figures.

The pressure sensing elements 420 are coupled to the processing module430 via sensor communication links 436. As an example, a sensorcommunication link 436 includes a wired communication link such as ametal trace on a printed circuit board, a wire, a dedicated data bus, ora shared data bus. In another example, a sensor communication link 436includes a wired communication path that is in accordance with a wiredcommunication protocol. The wired communication protocol includesRS-422, Inter-Integrated Circuit bus (I2C), serial peripheral interface(SPI), microwire, 1-wire, etc.

As another example, a sensor communication link 436 includes aninductive communication path in accordance with a near fieldcommunication (NFC) communication protocol. As yet another example, asensor communication link 436 includes a light communication base inaccordance with a light-based communication protocol (e.g., Infrared,fiber optics, etc.). As a further example, a sensor communication link436 includes a radio frequency (RF) communication path in accordancewith a standardized wireless communication protocol (e.g., 60 GHz,Bluetooth, WLAN, ZigBee, etc.) or in accordance with a proprietarywireless communication protocol.

The accelerometer 422 is coupled to the processing module 430 via anaccelerometer communication link 438. The accelerometer communicationlink 438 includes a wired communication link, a wired communication pathin accordance with a wired communication protocol, an inductivecommunication path in accordance with a near field communication (NFC)communication protocol, a light communication base in accordance with alight-based communication protocol, and/or a radio frequency (RF)communication path in accordance with a wireless communication protocol.

In an example of operation, the power source circuit 426 generates oneor more supply voltages 440 that powers the other devices of the controlcircuit 424. In an embodiment, the accelerometer 422 is on a commonprinted circuit board with the control circuit 424 and is powered by oneof the supply voltages. In another embodiment, the accelerometer 422 ison a separate printed circuit board from the control circuit 424 and ispowered by a power supply on the separate printed circuit board. In yetanother embodiment, the accelerometer 422 is on a separate printedcircuit board from the control circuit 424 but receives one of thesupply voltages 440 via the accelerometer communication link 438.

In an embodiment, each of the pressure sensing elements are activedevice and receive one of the supply voltages 440 via their respectivesensor communication link 436. In another embodiment, each of thepressure sensing elements are active device and receive one of thesupply voltages 440 are passive devices and include a power harvestingcircuit to generate a local supply voltage. In yet another embodiment,each of the pressure sensing elements are active device on a flexiblecircuit board, which includes a local power supply to generate the localsupply voltage.

In an example embodiment, the power source circuit 426 includes abattery-powered power supply. The power supply is a DC-to-DC converterand/or a linear regulator. In another example, the power source circuit426 includes the battery-powered power supply and a wired batterycharger. In this example, the battery charger is connected via a wire tothe battery of the battery-powered power supply for charging. In aspecific example, the shoe includes a connector or plug that isaccessible from the heel of the shoe. The battery charger is an externaldevice that plugs into the connector. In yet another example, the powersource circuit 426 includes the battery-powered power supply and awireless battery charger. In a further example, the power source circuit426 includes a radio frequency (RF) power harvesting circuit; an exampleof which will be described with reference to one or more subsequentdrawings.

Continuing with the example of operation, the clock circuit 428generates a clock signal 442. The clock signal 442 may be a sinusoidalsignal, a pulse pattern, a square wave signal, or other type of signalhaving a clock rate (e.g., 10 KHz to 10 GHz). The sampling signalgenerator 435 generates one or more sampling signals 444 from the clocksignal 442. For example, the sampling signal generator 435 is a buffersuch that the sampling signal 444 is a buffered version of the clocksignal 442. As another example, the sampling signal generator 435 is aphase locked loop (PLL) that multiples the rate of the clock signal 442such that the sampling signal 444 has a rate that is “x” times the rateof the clock signal 442, where “x” is greater than 1.

As yet another example, the sampling signal generator 435 divides therate of the clock signal 442 such that the sampling signal 444 has arate that is “y” times the rate of the clock signal 42, where “y” isgreater than 1. As a further example, the sampling signal generator 435includes a digital delay line to create one or more sampling signals 444from the clock signal. As a still further example, the sampling signalgenerator 435 includes a PLL and a digital delay line.

Continuing with the example of operation, the processing module 430samples, in accordance with the sampling signal 444, data (e.g., adigital value or analog voltage representing a pressure being sensed)from the pressure sensing element to produce foot force data 446. Theprocessing module 430 also samples, in accordance with the samplingsignal 444, data (e.g., x-y-z coordinate data or polar coordinate data)from the first accelerometer to produce three-dimensional (3D) foot data448. The processing module 430 may store the foot force data 446 and the3D data in memory 432 and/or provide it to the wireless communicationtransceiver 434 for transmission to the computing device.

In an embodiment, the control circuit is on a printed circuit board(PCB) that is positioned within a hole of the midsole, is in the dongle,and/or is included in the insole. The PCB may be secured into the holewith an adhesive, with an encasing material, etc. The PCB is a singlelayer printed circuit board (PCB), a multiple layer PCB, a rigid PCB, aflexible PCB, a high frequency PCB, and/or an aluminum-backed PCB.

In another embodiment, the control circuit is on a printed circuit board(PCB) that is positioned within the dongle 415. The accelerometer 422may be on the PCB with the control circuit and thus positioned withinthe hole of the midsole or within the dongle 415. In yet anotherembodiment, the accelerometer 422 is on a separate PCB from that of thecontrol circuit 424. In one permeation of this embodiment, theaccelerometer 422 is positioned within a second hole of the midsoleregardless of whether the control circuit PCB is within the hole of themidsole or in the dongle.

FIG. 71 is a logic diagram of an example of a method executed by aprocessing module that may be implemented as operational instructionsstored on a computer readable memory. The method begins at step 460where the processing module (e.g., processing module 430 of the shoesensor system 416 and/or processing module 427 of computing device 425)obtains foot force data. The foot force data created by sampling, inaccordance with a sampling signal, data from the pressure sensingelements of a shoe sensor system.

On a per sample basis, the foot force data includes, from at least someof the pressure sensing elements, a pressure sensor indicator (e.g., anidentifier of the particular pressure sensing element providing thedata) and one or more of a pressure sensed value, a representation ofthe sensed pressure level, and a pressure measurement. As an example, apressure sensing element generates a resistance from a resistivepressure sensor, a capacitance from a capacitance pressure sensor, aninductance from an inductor pressure sensor, or a frequency from apiezoelectric pressure sensor in response to an applied pressure. Theresistance, the capacitance, the inductance, or the frequency isprovided as the pressure sensed value (i.e., raw data of a pressuremeasurement).

The representation of the sensed pressure level is a digital value froma range of digital values or an analog voltage from a range of analogvoltages that based on the resistance, the capacitance, the inductance,or the frequency generated by the pressure sensing element. For example,a five-bit digital value includes a range from 0-31 (decimal), where 0corresponds to no pressure and 31 corresponds to maximum pressure of thepressure sensor. The representation of the sensed pressure level is nota pressure measurement, but a value in a range of values. The pressuremeasurement converts the representation of the sensed pressure levelinto an actual pressure measurement. As such, over a plurality ofsamples, the foot force data 446 includes, from each of at least some ofthe pressure sensing elements, the pressure sensor indicator and one ormore of a plurality of pressure sensed values, a plurality ofrepresentations of sensed pressure levels, and a plurality of pressuremeasurements.

As an example of one sampling interval, assume that a resistive pressuresensor of the pressure sensing element has a maximum pressure of 200pounds. For one sample, the resistive pressure sensor generates aresistance of 1,500 Ohms, where the resistance ranges from 100,000 Ohmswith no pressure to 500 Ohms with 200 pounds of pressure. The 1,500 Ohmsis converted to a digital value of 11000 (e.g., 24 in a digital scale of0 to 31). The digital value is then converted in a pressure measurementof 150 pounds via a look up table or other type of calculation.

The method continues at step 462 where the processing module obtainsthree-dimensional (3D) foot data. The 3D foot data is created bysampling, in accordance with the sampling signal, data from a firstaccelerometer of the shoe sensor system. On a per sample basis, the 3Dfoot data includes an accelerometer identifier (e.g., an ID of the firstaccelerometer) and one of an x-y-z coordinate value, a representation ofan x-y-z coordinate, and an x-y-z coordinate. The 3D foot data mayfurther include an x-y-z origin coordinate. As such, over a plurality ofsamples, the 3D foot force data includes the accelerometer identifierand one of a plurality of x-y-z coordinate values, a plurality ofrepresentations of x-y-z coordinates, and a plurality of x-y-zcoordinates.

As an example, the x-y-z origin coordinate is the origin of a referenceCartesian coordinate system corresponding to one of the shoes.Typically, when the shoe sensor is initialized to monitor a physicalactivity, an origin will be established based on a current location ofthe shoe for the reference Cartesian coordinate system. An x-y-zcoordinate value is the raw data generated by the accelerometer for agiven sample interval; the raw data includes a current x-axisacceleration, a current y-axis acceleration, and a current z-axisacceleration. A representation of the coordinate value is conversion ofthe raw accelerometer data into a x-y-z distance data based on theequation, for the x-axis) x=v0t+½at2, where x is the distance in thex-axis direction, t is the time interval, v0 is the initial velocity,and a is the acceleration in the x-axis. From the x distance, ydistance, and z distance and the x-y-z coordinate of the previous sample(or the origin coordinate if this is the first sample interval) thecurrent coordinate is determined, which corresponds to the x-y-zcoordinate.

With respect to steps 460 and 462, in one embodiment, the processingmodule of the shoe sensor system obtains the foot force data byreceiving it from the plurality of pressure sensing elements and obtainsthe three-dimensional foot data by receiving it from the firstaccelerometer. In another embodiment, the processing module of acomputing device obtains the foot force data includes by receiving itfrom a transmitter of the wireless communication transceiver and obtainsthe three-dimensional foot data by receiving it from the transmitter.

The method continues at step 464 where the processing module correlatesthe foot force data and the three-dimensional foot data in accordancewith the sampling signal to produce correlated foot data. In an exampleembodiment, the processing module of the shoe sensing system correlatesthe foot force data and the foot three-dimensional data to producecorrelated foot data and the wireless communication transceivertransmits the correlated foot data within the outbound RF signals to thecomputing device.

The method continues at step 466 where the processing module processingthe correlated foot data to determine physical activity data. Thephysical activity data includes, as will be subsequently discussed,distance traveled during a time period, stride length data, time,fatigue indication, injury prevention indicators, elevation tracking forthe time period, running optimization, and rotational sportoptimization.

In furtherance of the processing, the processing module adjusts theprocessing of the correlated foot data based on known nature of aphysical activity. The known nature of the physical activity includespredicable motions of body parts (e.g., how the feet, legs, hands, arms,torso, and head move when running or walking; how the body is supposedto move when hitting a golf ball; how the body is supposed to move whenthrowing a ball or hitting a ball with a racket or a bat; etc.). Theknown nature of the physical activity may further be enhanced to accountfor age of the person engaging in the physical activity, the skill levelof the person, and/or other personal characteristics that may affectperformance of the physical activity (e.g., injuries, flexibility,height, weight, etc.).

As an example of adjusting of the processing, the processing moduleadjusts the rate of the sampling signal. For instance, when the physicalactivity is walking, less data points are needed than when the person issprinting or jogging. As another example, the processing module usingphysical activity general movement data to enhance correlation of thefoot force data and the foot three-dimensional data. As yet anotherexample, the processing module using the physical activity generalmovement data to further determine the one or more of: the distancetraveled during a time period, the stride length data, the timeduration, the fatigue indication, the injury prevention indicators, theelevation tracking for the time period, the running optimization, andthe rotational sport optimization.

As a still further example, the processing module using previous data ofa wearer to determine the one or more of: the distance traveled during atime period, the stride length data, the time duration, the fatigueindication, the injury prevention indicators, the elevation tracking forthe time period, the running optimization, and the rotational sportoptimization. For example, if the person has a history of averaging 6mph when jogging with an average stride length of 3 feet, then the shoesensor system can be tuned to expect a pace of 6 mph and a stride lengthof about 3 feet, which will help improve accuracy of detecting footstrikes, etc.

FIG. 72 is an example of timing and data diagram of a shoe sensorsystem. The timing includes the sampling signal 444 that has a squarewave 50% duty cycle clock and a sampling rate (e.g., 500 Hz to 50 KHz).The sampling clock 444 may have an alternative waveform (e.g.,sinusoidal, a rectified sinusoidal signal, etc.) and may have analternate duty cycle (e.g., 10% to 90%). With each sampling interval(e.g., sample 1, 2, 3, 4, etc.), each of the pressure sensing elements420 and the accelerometer 422 provide data. The data may be 4-32 bitsper element 420 and from the accelerometer 422 per sample interval.

The pressure sensing elements 420 provide the foot force data 446 andthe accelerometer provides the 3D foot data 448. For each sampleinterval (e.g., sample 1, 2, 3, 4, etc.), the processing module 430 ofthe shoe sensor system correlates the foot force data 446 and the 3Dfoot data 448 to produce the correlated data 452. The correlation of thedata 446 and 448 may be an aggregation of the data on a per samplinginterval. For example, a data packet for sample 1 includes the footforce data 446 sampled from each of the pressure sensing elements takingduring sampling interval 1, an ID for each of the pressure sensingelement tied to their respective data, the 3D foot data from theaccelerometer sampled during sampling interval 1, and an ID for theaccelerometer tied to its data.

As another example of correlation, the processing module identifies afirst foot force data point of the foot force data (i.e., the data fromeach of the pressure sensing elements sampled during the first samplinginterval) and a first three-dimensional foot data point of thethree-dimensional foot data (i.e., the data from the accelerometersampled during the first sampling interval). The processing module thenlinks the first foot force data point with the first three-dimensionalfoot data point for the first sampling interval. The linking includesaggregation, aggregation and encryption, aggregation and scrambling,forward error correction such as Reed Solomon, and/or common packetidentifiers. For example, the data from each of the pressure sensingelements 420 and the accelerometer 422 is transmitted in its own datapacket that includes the data, an ID of the device associated with thedata, and a sampling interval indicator (e.g., a sampling intervalnumber, a clock count, a timestamp, etc.). The processing module linksthe foot force data points and the 3D foot data for each of the othersampling intervals in a similar manner.

FIG. 73 is another example of timing and data diagram of a shoe sensorsystem. The timing includes a first sampling clock 445 and a secondsampling clock 447. In this example, the second sampling clock 447 has arate that is approximately twice that of the first sampling clock 445.The sampling clocks 445 and 447 are synced. The first sampling clock 445is used to sample the data from the accelerometer 422 and the secondclock 447 is used to sample the data from the pressure sensing modules420.

As such, each of the pressure sensing elements produce two data samplesper one data sample of the accelerometer. The data is correlated basedon the slower clock signal such that, for each sampling interval of thefirst sampling clock 445, the correlated data includes two data samplesfrom each of the pressure sensing elements and one data sample from theaccelerometer.

FIG. 74 is another example of timing and data diagram of a shoe sensorsystem. The timing includes a first sampling clock 445 and a secondsampling clock 447. In this example, the second sampling clock 447 has arate that is approximately five times that of the first sampling clock445. The sampling clocks 445 and 447 are synced. The first samplingclock 445 is used to sample the data from the accelerometer 422 and thesecond clock 447 is used to sample the data from the pressure sensingmodules 420.

During the first sample interval of the first clock 445, there are fivecycles of the second sampling clock 447. A first cycle of the secondsampling clock 447 is used to sample the first pressure sensing element;a second cycle is used to sample a second pressure sensing element; athird cycle is used to sample a third pressure sensing element; a fourthcycle is used to sample a fourth pressure sensing element; and a fifthcycle is used to sample a fifth pressure sensing element. As such, eachof the pressure sensing elements produce one data sample per one datasample of the accelerometer. The data is correlated based on the slowerclock signal such that, for each sampling interval of the first samplingclock 445, the correlated data includes one data sample from each of thepressure sensing elements and one data sample from the accelerometer.

FIG. 75 is another example of timing and data diagram of a shoe sensorsystem. The timing includes a first sampling clock 445 and a pluralityof second sampling clocks 447. In this example, each of the secondsampling clock 447 has the same rate as the first sampling clock 445.The sampling clocks 445 and 447 are synced and the second samplingclocks are offset in time. The first sampling clock 445 is used tosample the data from the accelerometer 422 and the second clocks 447 areused to individually sample the data from the pressure sensing modules420.

A first of the second sampling clocks 447 is used to sample the firstpressure sensing element; a second of the second sampling clocks 447 isused to sample a second pressure sensing element; a third of the secondsampling clocks 447 is used to sample a third pressure sensing element;a fourth of the second sampling clocks 447 is used to sample a fourthpressure sensing element; and a fifth of the second sampling clocks 447is used to sample a fifth pressure sensing element. As such, each of thepressure sensing elements produce one data sample per one data sample ofthe accelerometer. The data is correlated based on the slower clocksignal such that, for each sampling interval of the first sampling clock445, the correlated data includes one data sample from each of thepressure sensing elements and one data sample from the accelerometer.

FIGS. 76A and 76B are top view diagrams of an example of positioningpressure sensing elements 420 within a pair of shoes. In this example,the pattern includes a first pressure sensing element 420-1 in a lateralheel position; a second pressure sensing element 420-2 in a medial heelposition; a third pressure sensing element 420-3 in a lateral ball offoot position; a fourth pressure sensing element 420-4 in a lateral toeposition; a fifth pressure sensing element 420-5 in a medial ball offoot position; and a sixth pressure sensing element 420-6 in a medialtoe position.

In contrast to most foot force analysis systems, the present systemincludes pressure sensors in selected area, not across the entiresurface area of the foot. Further, with the wireless features andmodular design, it does not require any modules to be strapped on to thelegs or the waist. Still further with a combination of pressures sensorsand accelerometers, accurate physical activity data is obtained; notapproximate data based on algorithms that predict physical activity froma few trigger points (e.g., arm movement for determine number of stepsand to determine a distance traveled. Such approximations have atolerance of about +/−10%. With the present system using measuredphysical activity data, the results will have a tolerance less than+/−1%.

FIGS. 77A and 77B are top view diagrams of another example ofpositioning pressure sensing elements 420 within a pair of shoes. Thisexample is similar to the one of FIGS. 76A and 76B with the addition oftwo more pressure sensing elements 420 per shoe. Each shoe includes aseventh pressure sensing element in a mid-ball of foot position 420-7and an eighth pressure sensing element 420-8 in a mid-toe position.

FIGS. 78A and 78B are top view diagrams of an example of the pressuresensing elements 420 positioned with respect to an insole 474-R of aright shoe and the control circuit board 470-R positioned with respectto a midsole 472-R of a right shoe. FIG. 78A illustrates the insole474-R with six pressure sensing elements 420-1 through 420-6 positionedas shown in FIG. 78B. In an embodiment, each of the pressure sensingelements 420 is attached to the surface of the insole 474-R via anadhesive or other bonding agent. In another embodiment, each of thepressure sensing elements 420 is fabricate into the insole 474-R as theinsole is manufactured. In another embodiment, the pressure sensingelements 420 are fabricated on a flexible printed circuit board thatoverlays and/or is adhered to the top surface of the insole 474-R.

FIG. 78B illustrates the midsole 472-R in which the control circuitboard 470-R is mounted. The control circuit board 470-R includes thepower source (PS), memory (M), a processing module (PM), a wirelesstransceiver (XCVR), an accelerometer (A), and a clock circuit (CL). Inan embodiment, the control circuit board 470-R is positioned within ahole in the midsole 472-R, where the hole does not extend all thethrough the midsole and is just deep enough to engulf the controlcircuit board. Once the control circuit board 470-R is positioned in thehole, it is held in place by an adhesive, a bonding agent, an encasingmaterial, etc.

Electrical coupling between the pressure sensing elements 420 and thecontrol circuit board is accomplished in a variety of ways. As anexample, the control circuit board includes an electrical connector thatmates to a corresponding electrical connector coupled to the pressuresensing elements. The connectors are positioned in the insole andmidsole respectively as to provide minimal interference with the fit andcomfort of the shoe.

As another example, the control circuit board 470-R is coupled to thepressure sensing elements via RF signals. One or more examples of RFcoupling will be described with reference to one or more subsequentFigures. As yet another example, the control circuit board 470-R iscoupled to the pressure sensing elements via NFC coils. One or moreexamples of NFC coupling will be described with reference to one or moresubsequent Figures.

FIGS. 79A and 79B are identical to FIGS. 78A and 78B, but FIGS. 79A and79B are for the left shoe. As such, these Figures area top view diagramsof an example of the pressure sensing elements 420 positioned withrespect to an insole 474-L of a left shoe and the control circuit board470-L positioned with respect to a midsole 472-L of a left shoe.

FIG. 80A is similar to FIG. 79B with the accelerometer (A) being on aseparate circuit board 478-L from the control circuit board 476-L. In anexample, the accelerometer circuit board 478-L is coupled to the controlcircuit board 476-L via a wired connection. In another example, theaccelerometer circuit board 478-L is coupled to the control circuitboard 476-L via a wireless connection.

FIG. 80B is identical to FIG. 80A but it is for the right midsole 472-Rand includes an accelerometer circuit board 478-R and a control circuitboard 476-R.

FIG. 81A is similar to FIG. 80A with the addition of a secondaccelerometer on another circuit board 480-L. In an example, theaccelerometer circuit board 480-L is coupled to the control circuitboard 476-L via a wired connection. In another example, theaccelerometer circuit board 480-L is coupled to the control circuitboard 476-L via a wireless connection. Note that the secondaccelerometer is positioned within the pattern of the foot and is at adistance from the first accelerometer.

In an example of operation, the second accelerometer provides secondx-y-z coordinates (i.e., second 3D foot data) at a sample rate of thesampling signal to the processing module (PM). Recall that the firstaccelerometer provides first x-y-z coordinates at the sample rate to theprocessing module (PM). The processing module correlates the foot forcedata, the three-dimensional foot data, and the second three-dimensionalfoot data in accordance with the sampling signal to produce thecorrelated foot data.

The processing module (e.g., of the circuit board and/or of thecomputing devices) processes the first and second x-y-z coordinates toproduce foot orientation data. For example, for a given samplinginterval, the first x-y-z coordinates are processed to determine a firstlocation of the first accelerometer and the second x-y-z coordinates areprocessed to determine a second location of the second accelerometer.With the distance between the first and second accelerometers known, theorientation of the foot is determined.

Each of the accelerometer boards 476-L and 478-L require power and aclock signal or sampling signal. In an embodiment, each board 476-L and478-L includes its own power source circuit and clock circuit togenerate the sampling signal. In another embodiment, each board 476-Land 478-L receives a power supply and a clock signal or sampling signalfrom the control circuit board 470-L. In yet another embodiment, eachboard 476-L and 478-L includes its own power source circuit and receivesthe clock or sampling signal from the control circuit board 470-L.

FIG. 81B is identical to FIG. 81A but it is for the right midsole 472-Rand includes accelerometer circuit board 478-R, accelerometer circuitboard 480-R, and a control circuit board 476-R.

FIG. 82 is a side view diagram of another example of the pressuresensing elements 420 positioned with respect to an insole 474 of a shoe(e.g., left or right foot) and the control circuit board 76 andaccelerometer (A) positioned with respect to a midsole 474 of the shoe.The shoe is further shown to include an outsole 473.

Each of the pressure sensing elements 420-1, 420-3, and 420-4 and theothers not shown are positioned at or on the surface of the insole 474.Pressure sensing element 420-1 (and 420-2 not shown) are positioned inthe heel section of the shoe; pressure sensing element 420-3 (and 420-5not shown) are positioned in the ball of foot section of the shoe;pressure sensing element 420-4 (and 420-6 not shown) are positioned inthe toe section of the shoe. The accelerometer (A) may be on the samePCB and the control circuit (i.e., board 476) or on its own PCB (i.e.,board 478).

FIG. 83 is a front view diagram of another example of the pressuresensing elements 420-4 and 420-6 positioned with respect to an insole474 of a shoe that also includes the midsole 472, the outsole 473, andan upper section 475. In this example, pressure sensing elements 420-4is positioned on the lateral side of the shoe (e.g., approximately underthe little toe or at the fifth metatarsal) and pressure sensing elements420-6 is positioned on the medial side of the shoe (e.g., approximatelyunder the big toe or at the first metatarsal).

FIG. 84 is a rear-view diagram of another example of the pressuresensing elements 420-1 and 420-2 positioned with respect to an insole474 of a shoe that also includes the midsole 472 and the outsole 473. Inthis example, pressure sensing elements 420-1 is positioned on thelateral side of the shoe (e.g., approximately under the outside of theheel) and pressure sensing elements 420-2 is positioned on the medialside of the shoe (e.g., approximately under the inside of the heel).

FIG. 85 is similar to FIG. 82 with the addition of pressure sensingelements positioned in the outsole 473. Assuming this a lateral sideview of the shoe, pressure sensing element 420-9 is located underneathpressure sensing element 420-1 and is positioned at or near the surfaceof the outsole 473. Similarly, pressure sensing element 420-10 islocated underneath pressure sensing element 420-3 and is positioned ator near the surface of the outsole 473 and pressure sensing element420-11 is located underneath pressure sensing element 420-4 and ispositioned at or near the surface of the outsole 473. The medial sidemay also include pressure sensing elements in the outsole 473 thatmirror the top perspective positions of pressure sensing elements 420-2,420-5, and 420-6.

With pressure sensing elements in both the insole 474 and outsole 473,pressure exerted by the foot into the can be measured as well as thepressure exerted by the shoe on to the ground or surface. With thisdata, the energy transfer effectiveness and energy transfer function ofthe shoe can be determined. For example, the energy transfereffectiveness measures the loss of energy as a result of the shoe. Asanother example, the energy transfer function corresponds to how theshoe transfers energy from the insole to the midsole.

FIG. 86 is a logic diagram of an example of generating foot force data.The method begins at step 700 where the processing module of a forcedetection system receives first data regarding a first set of pressuresensors, which are positioned in an insole of a shoe. In an example, thefirst set of pressure sensors includes a set of variable capacitors, andthe system includes a first set of drive sense circuits coupled thereto.

The method continues at step 710 where the processing module generates afirst digital representation of the first data. The method continues atstep 702 where the processing module receives second data regarding asecond set of pressure sensors, which are positioned in an outsole of ashoe. The method continues at step 703 where the processing modulegenerates a second digital representation of the second data. Theprocessing module then writes the digital representations of the firstand second data to memory.

In an example, a first pressure sensor of the first set of pressuresensor is positioned in a ball of foot section of the insole and a firstpressure sensor of the second set of pressure sensors positioned in aball of foot section of the outsole. From a lateral side view, a frontview, and a top view, the first pressure sensors of the first and secondsets of pressure sensors are substantially aligned. In another example,a pressure sensor of the second set of pressure sensors includes avariable capacitor, a variable inductor, a variable resistor, and/or apiezoelectric transducer.

FIG. 87 is a logic diagram of another example of generating foot forcedata. An example method begins at step 704, where a processing module ofa force detection system and/or by a processing module of a computingentity obtains, first x, y, and z force component data of a firstpressure sensor when active in a shoe. The method continues at step 705where the processing module obtains second x, y, and z force componentdata of a second pressure sensor of the force detection system whenactive in the shoe.

The method continues at step 706 where the processing module determinesmagnitude and direction of force traversing through at least a portionof a sole of the shoe based on the first and/or second x, y, and z forcecomponent data. For example, the processing module determines themagnitude and the direction of the force traversing through the at leastthe portion of the sole based on the second x, y, and z force componentdata. As another example, the processing module determines force loss ofthe at least the portion of the sole based on a difference between thefirst and second x, y, and z force component data.

FIG. 88 is a schematic block diagram of another example of generatingfoot force data. In this example, the first sensor in the insole has anangular force applied to it. The angular force includes an x componentand a y component, from this perspective. The second sensor in theoutsole has a second angular force applied to it. In this example, the ycomponent of the angular force on the second sensor is less than the ycomponent of angular force on the first sensor. This different is usedto calculate the angle of the force traversing through the shoe, whichcan then be used to determine angle and/or magnitude of the forceapplied to the first sensor.

FIG. 89 is a schematic block diagram of another example of generatingfoot force data. This example is similar to that of FIG. 88 with adifference being that the second sensor is in a mat and not in theoutsole. The sensed data can be used to determine the angle and/ormagnitude of the force applied to the first sensor.

FIG. 90 is a schematic block diagram of another example of generatingfoot force data that detects horizontal movement and/or horizontal tiltof the foot within the shoe. In this example, the first sensor is on themedial side of the shoe and the second sensor is on the lateral side ofthe shoe. With more horizontal force component in the lateral side ofthe shoe than the medial side indicates that the foot is sliding and/ortilting towards the lateral side of the shoe, which is most oftenundesirable in athletics.

FIG. 91 is similar to FIG. 83 with the addition of a pressure sensingelement 420-12 being positioned on the lateral wall of the shoe. Theshoe may include more than one pressure sensing element along thelateral wall. With one or more pressure sensing elements along thelateral wall of the shoe, horizontal forces can be measured as theperson is cutting, making a lateral movement, etc. while wearing theshoes.

FIG. 92 is similar to FIG. 91 with the addition of a pressure sensingelement 420-13 being positioned on the medial wall of the shoe. The shoemay include more than one pressure sensing element along the medialwall. With one or more pressure sensing elements along the medial wallof the shoe, horizontal forces in both directions can be measured as theperson is cutting, making a lateral movement, etc. while wearing theshoes.

FIG. 93 is a schematic block diagram of another embodiment of a shoesensor system 416 R & L. In this embodiment, the system 416 furtherincludes a gyroscope 480 that is coupled to the processing module of thecontrol circuit 424 via a gyroscope communication link 482. Thegyroscope communication link 482 is one or more of a wired communicationlink (e.g., a wire), a wired communication path in accordance with awired communication protocol, an inductive communication path inaccordance with a near field communication (NFC) communication protocol,a light communication base in accordance with a light-basedcommunication protocol and a radio frequency (RF) communication path inaccordance with a wireless communication protocol.

The gyroscope 480 may be on the same PCB as the control circuit 424, maybe on a separate PCB with the accelerometer, or on its on PCB positionedwithin the shoe. Regardless of its inclusion of a PCB, the gyroscopegenerates pitch, yaw, and roll coordinates. The processing module 30samples, in accordance with the sampling signal 444, the pitch, yaw, androll coordinates to produce pitch, yaw, and roll data. The processingmodule 430 also correlates the pitch, yaw, and roll data with the footforce data 446 and the 3D foot data to produce the correlated data. Thewireless communication transceiver 434 transmits the outbound RF signals450, which includes the correlated data.

FIG. 94 is a schematic block diagram of another embodiment of a shoesensor system 416 R & L. In this embodiment, the system 416 furtherincludes a biometric sensor 484 that is coupled to the processing moduleof the control circuit 424 via a biometric communication link 486. Thebiometric communication link 486 is one or more of a wired communicationlink (e.g., a wire), a wired communication path in accordance with awired communication protocol, an inductive communication path inaccordance with a near field communication (NFC) communication protocol,a light communication base in accordance with a light-basedcommunication protocol and a radio frequency (RF) communication path inaccordance with a wireless communication protocol.

The biometric sensor 484 is on, or in, the surface of the insole tomeasure a biometric condition of the person wearing the shoes via theperson's feet. For instance, the biometric condition includes one ormore of heart rate, perspiration, respiration, temperature, etc. Assuch, the biometric sensor 484 generates biometric indicators regardingone or more of heart rate, moisture level, respiration, and temperature.

The processing module 430 samples, in accordance with the samplingsignal 444, the biometric indicators to produce biometric data. Theprocessing module 430 also correlates the biometric data with the footforce data 446 and the 3D foot data to produce the correlated data. Thewireless communication transceiver 434 transmits the outbound RF signals450, which includes the correlated data.

To improve the connectivity of the biometric sensor 484 to the skin ofthe person wearing the shoes, the person may wear socks with metallicthread in the bottom of the sock. The metallic thread is woven into thesock at one or more locations that corresponds to the position of thebiometric sensor. Note that each shoe may include a plurality ofbiometric sensors, each measuring a different biometric condition.

FIG. 95 is a schematic block diagram of another embodiment of a shoesensor system 416 R & L that wirelessly communicates with the computingdevice 425. The system 416 includes pressure sensor elements 420-1through 420-x, an accelerometer 422, sensor communication circuit 504, adata bus 598, a power bus 510, a communication bus 502, a power sourcecircuit 424, a clock circuit 428, a processing module 430, memory 432, awireless communication transceiver 344, a sampling signal generator 435,a battery 496, a connector set 492 & 494, and a battery charger 496.

Each of the buses 498, 500, and 502 includes a single shared link, aplurality of shared links, a plurality of individual links, or acombination thereof. A link is a wired communication link (e.g., awire), a wired communication path in accordance with a wiredcommunication protocol, an inductive communication path in accordancewith a near field communication (NFC) communication protocol, a lightcommunication base in accordance with a light-based communicationprotocol and a radio frequency (RF) communication path in accordancewith a wireless communication protocol.

The pressure sensor elements 420-1 through 420-x, the accelerometer 422,the power source circuit 424, the clock circuit 428, the processingmodule 430, the memory 432, the wireless communication transceiver 434,and the sampling signal generator 435 function as previously describedwith reference to one or more of the preceding figures and/or as will bedescribed with reference to one or more of the subsequent figures.

The battery 490 is a rechargeable battery that powers the power supplycircuit 426, which produces one or more supply voltages. The battery 490is recharged by the battery charger 96, which may be an external deviceto the shoe or including within the shoe. In the example, shown, thebattery charger 496 is an external device that is connected to thebattery 490 via connectors 492 and 494. In an embodiment, the connectors492 and 494 are wired connectors that provide electrical coupling viawires, pins, receptacles, etc. In another embodiment, the connectors 492and 494 are wireless to provide NFC wireless charging. Note that theconnector may be in the heel section of the shoe and positioned to notinterfere with wearing of the shoes.

FIG. 96 is a top view diagram of an example of the pressure sensingelements 420 that are RF coupled to the control circuit 424. Eachpressure sensing element 420 is one the insole 474 and associated withan antenna 510-1 through 510-6, where pressure sensing element 420-1 isassociated with antenna 510-1 and so on. With reference to FIG. 97,which is a side view diagram of the shoe, the pressure sensing elementantennas 510 are positioned over a midsole antenna 512. The midsoleantenna 512 is coupled to the control circuit 424.

In an example of operation, the wireless transceiver (XCVR) is in afirst mode to wirelessly communicate with the pressure sensing elements420. In the first mode, the wireless transceiver generates a low powerRF signal that includes a continuous wave portion to enable passivepressure sensing elements 420 to produce a supply voltage that powersthe sensing element 420. The transceiver then generates RF controlsignals requesting the pressure sensing elements 420 to respond withtheir pressure sensing measurements.

After the control circuit 424 has gathered sufficient pressure sensingmeasurements from the sensing elements, the transceiver switches to asecond mode to communicate the correlated data to the computing device425. The transceiver switches between the first and second modes togather data and to provide the data to the computing device. Note thatthe frequency used to communicate with the sensing elements may be thesame or different than the frequency used to communicate with thecomputing device and the frequency ranges from a few hundred Mega Hertzto 60 GHz or more. As a specific example, the transceiver communicateswith the computing device using a frequency of 2.4 GHz and communicateswith the sensing elements using 60 GHz.

FIG. 98 is a top and a side view diagram of an example of the pressuresensing element antennas 510 positioned with respect to the midsoleantenna 512. In this example, the antenna 512 has a surface area thatencompasses the surface area of the three (or more) pressure sensingelement antennas 510. In an example, the midsole antenna 512communicates with one pressure sensing element antenna 510 at a time. Inanother example, the midsole antenna 512 communicates with two or morepressure sensing element antennas 510 at the same time using a frequencydivision multiplexing scheme.

FIG. 99 is a top and a side view diagram of another example of thepressure sensing element antennas 510 positioned with respect tomultiple midsole antennas 512. In this example, each midsole antenna 512has a surface area that is about the same size as the surface area of apressure sensing element antenna 510. In an example, each midsoleantenna 512 communicates with a corresponding pressure sensing elementantenna 510 at a time using the same or different frequencies. Inanother example, each midsole antenna 512 communicates with itscorresponding pressure sensing element antennas 510 in a time divisionmultiplexing manner using the same or different frequencies.

FIG. 100 is a schematic block diagram of an embodiment of a pressuresensing element 420 that includes an antenna 510, a transmission line512, a power harvesting circuit 514, a clock circuit 516, a pressuresensor 518, memory 520, digital circuitry 522, a down converter 524, anup converter 526, a low noise amplifier (LNA) 528 and a power amplifier(PA) 530. The transmission line 512 coupled the antenna 510 to the powerharvesting circuit 514, the receiver 528, and the transmitter 530.Depending on the location of the antenna 510 and the pressure sensingelement with the shoe, the transmission line 512 may be a fewmillimeters long to tens of centimeters long.

In an example of operation, the antenna 510 receives an RF signal fromthe control circuit (via the transceiver 434 and/or anothertransceiver). The power harvesting circuit 514 converts the RF signalinto a supply voltage Vs, which powers the rest of the circuit. Oncepower is available, the pressure sensor 518 begins sensing pressure andprovides pressure sensory signals to the digital circuitry 522. Thedigital circuitry 522, which may be implemented as a processing module,converts the pressure sensory signals into the pressure sensed data inaccordance with a sampling clock generated by the clock circuit 516.

The up converter 526 converts the pressure sensed data into an RF signalthat is amplified by the PA 530 and transmitted by the antenna 510. Thedigital circuitry 522, the up converter 526, and/or the PA 530 may usebackscattering, Amplitude Shift Keying (ASK), Amplitude Modulation (AM),Frequency Shift Keying (FSK), and/or Phase Shift Keying (PSK) to convertthe pressure sensed data into a transmitted RF signal. Note that thememory 520 may store the pressure sensed data until it is transmitted ormay store the pressure sensed data indefinitely.

The pressure sensing element 420 may provide the pressure sensed data atpredetermined intervals or in response to a request for data. For thelatter, the antenna receives an inbound RF signal that is amplified bythe LNA 528 and down converted into a baseband signal via the downconverter 524. The digital circuitry 522 processes the baseband signalto identify the request for data.

FIG. 101 is a schematic block diagram of another embodiment of apressure sensing element 420 that is similar to the one of FIG. 100 withthe inclusion of a plurality of pressure sensors 518-1 through 518-3 (3are shown but could include more or less than 3). The pressure sensors518-1 through 518-3 may each be the same type of sensor (e.g.,resistive, capacitive, inductive, piezoelectric, etc.) to sense pressurein a same area or in different areas. In an example, the pressuresensors are of the same type and have different pressure ratings (e.g.,one from 10-100 force pounds, a second from 100-200 force pounds, and athird from 200-400 force pounds). In another example, the pressuresensors are of different types and of the same pressure ratings, whichcan be averaged and/or used for calibration.

FIG. 102 is a schematic block diagram of another embodiment of apressure sensing element 420 that is similar to the one of FIG. 100 withthe inclusion of multiple antennas 510-1 through 510-x, multipletransmission lines 512-1 through 512-x, and multiple power harvestingcircuits 514-1 through 514-x. In this embodiment, the multiple antennasand power harvesting circuits increase the power available for thepressure sensing element 420.

FIG. 103A is a schematic block diagram of a capacitive pressure sensor518 that includes a capacitor (e.g., plates 1 and 2 and a dielectric), acapacitance to voltage converter (C to V), and an analog to digitalconverter (ADC). In an alternative embodiment, the ADC is in the digitalcircuitry of the pressure sensing element of FIGS. 100-102 or in thecontrol circuit 424. When pressure is applied to the capacitor, thedielectric changes cause a capacitance change. The capacitance change isconverted to an analog voltage by the capacitance to voltage converter.The ADC converts the analog voltage into a digital value thatrepresented the pressure data.

FIG. 103B is a schematic block diagram of a resistive pressure sensor518 that includes a resistor (e.g., resistive plate), a resistance tovoltage converter (R to V), and an analog to digital converter (ADC). Inan alternative embodiment, the ADC is in the digital circuitry of thepressure sensing element of FIGS. 100-102 or in the control circuit 424.When pressure is applied to the resistive plate, its resistance changes.The resistive change is converted to an analog voltage by the resistanceto voltage converter. The ADC converts the analog voltage into a digitalvalue that represented the pressure data.

FIG. 103C is a schematic block diagram of an inductive pressure sensor518 that includes an inductor (e.g., a coil proximal to a ground plane),an inductance to voltage converter (L to V), and an analog to digitalconverter (ADC). In an alternative embodiment, the ADC is in the digitalcircuitry of the pressure sensing element of FIGS. 100-102 or in thecontrol circuit 424. When pressure is applied to the inductor, the coilis pressed closer to the ground plane causes an inductance change. Theinductance change is converted to an analog voltage by the inductance tovoltage converter. The ADC converts the analog voltage into a digitalvalue that represented the pressure data.

FIG. 103D is a schematic block diagram of a frequency pressure sensor518 that includes a piezoelectric transducer, a frequency to voltageconverter (F to V), and an analog to digital converter (ADC). In analternative embodiment, the ADC is in the digital circuitry of thepressure sensing element of FIGS. 100-102 or in the control circuit 424.When pressure is applied to the piezoelectric transducer, its resonatingfrequency changes. The frequency change is converted to an analogvoltage by the frequency to voltage converter. The ADC converts theanalog voltage into a digital value that represented the pressure data.

FIG. 104 is a top view diagram of an example of the pressure sensingelements 420 that are inductively coupled to the control circuit 424.Each pressure sensing element 420 is one the insole 474 and associatedwith an NFC coil 540-1 through 540-6, where pressure sensing element420-1 is associated with NFC coil 510-1 and so on. With reference to theside view diagram of FIG. 105, the pressure sensing element antennas 510are positioned over a midsole NFC transmission coil, which is coupled tothe control circuit 424. In the alternative and with reference to theside view diagram of FIG. 106, the pressure sensing element antennas 510are positioned over corresponding midsole NFC transmission coils, whichare coupled to the control circuit 424. The NFC coils may communicateusing frequencies ranging from tens of MHz to tens of GHz, or more.

FIG. 106 is a logic diagram of another example of a method executed by ashoe sensor system that begins at step 550 where the system determinesthe weight of the person wearing the shoes. For example, a person'sweight can be determined by having them stand on one foot, take forcemeasurements for this foot, stand on the other foot, and take forcemeasurements for the other foot. From the force measurements, weight iscalculated.

The method continues at step 552 where the system is calibrated ifneeded. For example, if the determination of a person's weight from theforce measurements differs from a weight measurement from a scale, thenthe system can be calibrated (e.g., change coefficients for forcemeasurements to weight conversion). Once the system is calibrated, themethod continues at step 554.

At step 554, the system determines whether it detects movement. If not,the system waits until movement is detected and stays in a low powermode (e.g., reduced supply voltage, lower clock rate, no sampling,etc.). When movement is detected (e.g., accelerometer data is detected,the person enables the system to start tracking physical activity,detecting foot forces that corresponds to movement, etc.). The methodthen continues at step 556 where the system produces correlated dataduring a game, practice, or other event.

The method continues at step 558 where the system or the computingdevice processing the in-game correlation data to produce physicalactivity monitoring data. Various examples of processing the correlateddata will be described with reference to one or more of FIGS. 107-116.The method continues at step 559 where the system or the computingdevice processes post game data. For example, the system or thecomputing device add the most recent game data to data from previousgames to produce historical data.

FIG. 107 is a logic diagram of another example of a method executed by ashoe sensor system to determine the distance traveled during the timeperiod (e.g., for the duration of the physical activity, a portion ofthe physical activity, etc.). The method begins at step 560 where theprocessing module (e.g., processing module 430 of the system and/orprocessing module 427 of the computing device 425) determines a firstx-y coordinate from a first three-dimensional foot data point (e.g.,from an x-y-z coordinate from the accelerometer) that corresponds to thebeginning of the time period. For example, the first x-y coordinatecorresponds to the first data sampled from the accelerometer when thesystem was activated to record physical activity data. As anotherexample, the first x-y coordinate corresponds to the first data sampledfrom the accelerometer at the start of a new time interval of thephysical activity monitoring.

The x-y coordinate of the x-y-z coordinate correspond to a position onthe surface of the ground and the z-coordinate of the x-y-x coordinatecorresponds to an up position with respect to the ground. The firstx-y-x coordinate corresponds to an original of a reference Cartesian orPolar coordinate system for tracking the distance the shoes travel.

The method continues at step 562 where the processing module determinesa next x-y coordinate from a next three-dimensional foot data point. Thenext 3D foot data point corresponds to the accelerometer data taking atthe next sampling interval, or point, of the sampling clock with respectto the previous sampling interval using absolute values to get anaccumulation of movement. For example, the first x-y-z coordinate wastaking at sampling interval 0, the second x-y-z coordinate was taking atsampling interval 1, the third x-y-z coordinate was taking at samplinginterval 2, and so on until the last sampling interval of the timeperiod.

The method continues at step 564 where the processing module determinesa next delta distance based on a difference between the first x-ycoordinate and the next x-y coordinate. For example, if the first x-ycoordinate is 0,0 and the second x-y coordinate is 0.5, 0.75, then thedelta distance includes a delta x of 0.5 and a delta y of 0.75. For thenext sampling interval, the third x-y coordinate is 0.65, 1.125. Assuch, the delta x from the second to third coordinate is 0.15 and thedelta y is 0.375. For each sampling interval, the delta distance may bestored for further and/or subsequent processing.

The method continues at step 566 where the processing module adds thenext delta distance to an accumulation of previous delta distances toproduce an updated accumulation of delta distances. For example, aftersampling interval 1, the processing module adds the new delta data of0.5 for delta x and 0.75 for delta y to the accumulated delta data(which is 0, 0 since the tracking process is just beginning). The resultof the adding yields an updated accumulated delta distance of 0.5, 0.75.Continuing with the example for sample interval 2, the new delta dataincludes 0.15 for delta x and 0.375 for delta y. Adding the new deltadata to the accumulated data yields an updated accumulated data of 0.65,1.125.

The method continues at step 668 where the processing module determineswhether the end of the time period has been reached. For example, theuser ends the tracking of physical activity. As another example,detecting a stoppage of the physical activity. As yet another example,detection of expiration of the time period. If the time period has notended, the method repeats at step 562 for the next data from the nextsampling interval. If the time period has ended, the method continues atstep 570 where the accumulated data is outputted as the distancetraveled during the time period.

FIG. 108 is a logic diagram of another example of a method executed by ashoe sensor system to determine stride length data. Stride length dataincludes one or more of maximum length, minimum stride length, averagestride length for the duration of the physical active, average stridelength for an interval of the overall duration, imbalances betweenleft-to-right stride and/or right-to-left stride, etc.

The method begins at step 580 where the processing module (e.g.,processing module 430 of the system and/or processing module 427 of thecomputing device 425) determines a first left x-y coordinate from afirst left three-dimensional foot data point that corresponds to a leftfoot being in contact with a surface (e.g., track, ground, court,sidewalk, road, etc.).

The method continues at step 582 where the processing module determinesa first right x-y coordinate from a first right three-dimensional footdata point that corresponds to a right foot being in contact with thesurface after the left foot has been in contact with the surface. Themethod continues at step 584 where the processing module determines aleft foot to right foot stride length based on the first left x-ycoordinate and the first right x-y coordinate. This can be repeated foreach step taking by the person wearing the shoes.

FIG. 109 is a logic diagram of another example of a method executed by ashoe sensor system to determine stride length data; in particular, rightto left stride data. The method begins at step 586 where the processingmodule (e.g., processing module 430 of the system and/or processingmodule 427 of the computing device 425) determines a first right x-ycoordinate from a first right three-dimensional foot data point thatcorresponds to a right foot being in contact with a surface (e.g.,track, ground, court, sidewalk, road, etc.).

The method continues at step 588 where the processing module determinesa first left x-y coordinate from a first left three-dimensional footdata point that corresponds to a left foot being in contact with thesurface after the right foot has been in contact with the surface. Themethod continues at step 590 where the processing module determines aright foot to left foot stride length based on the first right x-ycoordinate and the first left x-y coordinate. This can also be repeatedfor each step taking by the person wearing the shoes.

FIG. 110 is a logic diagram of another example of a method executed by ashoe sensor system to determine the time duration. The method begins atstep 600 where the processing module (e.g., processing module 430 of thesystem and/or processing module 427 of the computing device 425) countsclock cycle of the clock signal from a beginning of the time durationuntil an end of the time duration to produce a clock cycle count. Themethod continues at step 602 where the processing module interprets theclock cycle count in light of a clock rate of the clock signal todetermine the time duration. For example, if the clock rate is 100 Hz,the number of cycles is 10,000, then the time duration is 10,000/100 or100 seconds.

FIG. 111 is a logic diagram of another example of a method executed by ashoe sensor system to determine a fatigue indication. The fatigueindicator includes, but is not limited to, shortening of stride, paceslowing, change in foot forces, imbalance between left to right strideand right to left stride, etc. The method begins at step 604 where theprocessing module (e.g., processing module 430 of the system and/orprocessing module 427 of the computing device 425) detects, based onchanges in the correlated foot data over time within the time period,one or more of a shortening of stride length, a slowing of pace, and achange in foot force (e.g., more, less, more in heel, more on outsideedge, etc.). The method continues at step 606 where the processingmodule interprets the one or more of a shortening of stride length, aslowing of pace, and a change in foot force to determine a fatiguelevel.

FIG. 112 is a logic diagram of another example of a method executed by ashoe sensor system to determine one or more injury preventionindicators. An injury prevention indicator includes, but is not limitedto, recognize change in data that is likely caused by fatigue, cramping,muscle strain, imbalance in strides, imbalance in foot forces, etc.

The method begins at step 610 where the processing module (e.g.,processing module 430 and/or processing module 427 of the computingdevice 425) detects an abnormality based on changes in the correlatedfoot data over some period of time within the time period (e.g., frominterval to interval, at various time check points, etc.). Theabnormality includes, but is not limited to, an imbalance in foot forcebetween the feet, a change in foot forces of one or both feet, animbalance in stride lengths, an imbalance in stride height (e.g.,differing z components from stride to stride) between the feet, and footmovement outside of a movement deviation range (e.g., rolled ankle,dragging a foot, etc.).

The method continues at step 612 where the processing module interpretsthe abnormality to identify a potential injury (e.g., a potentialhamstring issue, a potential calf injury, etc.). The method continues atstep 614 where the processing module determines a preventive measurebased on the potential injury and/or the abnormality. For example, thepreventive measure is to restrict training to a maximum amount of timeper day. As another example, the preventive measure is to rest for acertain number of days. As yet another example, the preventive measureis to get treatment on the body part.

FIG. 113 is a logic diagram of another example of a method executed by ashoe sensor system to determine elevation tracking for the time periodwhile performing the physical activity (e.g., steps climbed, elevationchanges while running, walking, and/or hiking). The method begins atstep 616 where the processing module (e.g., processing module 430 and/orprocessing module 427 of the computing device 425) determines a first zcoordinate from a first three-dimensional foot data point (e.g., firstx-y-z coordinate as previously described) that corresponds to thebeginning of the time period.

The method continues at step 618 where the processing module determinesa next z coordinate from a next three-dimensional foot data point (e.g.,a next x-y-z coordinate as previously discussed) that corresponds to anext sampling point of the sampling clock within the time period. Themethod continues at step 620 where the processing module determines anext delta distance based on a difference between the first z coordinateand the next z coordinate. The method continues at step 622 where theprocessing module determines whether the next delta distance is greaterthan or equal to zero. When it is not, the method continues at step 618.

When the next delta distance is greater than or equal to zero, themethod continues at step 624 where the processing module adds the nextdelta distance to an accumulation of previous delta distances to producean updated accumulation of delta distances. The method continues to step2626 where the processing module determines whether the time period hasended. When the time period has not ended, the method repeats as step618.

When the next sampling point corresponds to the end of the time period,the method continues at step 628 where the processing module providesthe updated accumulation of delta distances as the elevation change thatoccurred during the time period. For example, the accumulated z distanceis 100 feet, which can be equated to ascending 10 flights of stairs.

FIG. 114 is a logic diagram of another example of a method executed by ashoe sensor system to determine negative elevation tracking (e.g.,descending) for the time period while performing the physical activity.The method begins at step 630 where the processing module (e.g.,processing module 430 and/or processing module 427) determines a first zcoordinate from a first three-dimensional foot data point (e.g., firstx-y-z coordinate as previously described) that corresponds to thebeginning of the time period.

The method continues at step 632 where the processing module determinesa next z coordinate from a next three-dimensional foot data point (e.g.,a next x-y-z coordinate as previously discussed) that corresponds to anext sampling point of the sampling clock within the time period. Themethod continues at step 634 where the processing module determines anext delta distance based on a difference between the first z coordinateand the next z coordinate. The method continues at step 636 where theprocessing module determines whether the next delta distance is lessthan or equal to zero. When it is not, the method continues at step 632.

When the next delta distance is less than or equal to zero, the methodcontinues at step 638 where the processing module adds the next deltadistance to an accumulation of previous delta distances to produce anupdated accumulation of delta distances. The method continues to step640 where the processing module determines whether the time period hasended. When the time period has not ended, the method repeats as step632.

When the next sampling point corresponds to the end of the time period,the method continues at step 642 where the processing module providesthe updated accumulation of delta distances as the elevation change thatoccurred during the time period. For example, the accumulated z distanceis −100 feet, which can be equated to descending 10 flights of stairs.

FIG. 115 is a logic diagram of another example of a method executed by ashoe sensor system to determine running optimization, which includes oneor more of proper foot positioning, proper weight distribution, balancedstrides, stride length training, increase ground reaction force, reducefoot to ground contact time, etc. The method begins at step 650 wherethe processing module (e.g., processing module 430 and/or processingmodule 427) determines whether there is a weight imbalance betweenstrides, over a number of strides, and/or over a period of time. Forexample, a weight imbalance is detected when more force is exerted whenone foot strikes the ground versus the other shoe. If yes, the methodcontinues at step 652 where the processing module adds weightdistribution issue to a list of running adjustment inputs.

When the weight distribution issue has been added to the runningadjustments inputs or there is not a weight distribution issue, themethod continues at step 654 where the processing module determineswhether a stride length imbalance exists. If yes, the method continuesat step 656 where the processing module adds stride length imbalanceissue to a list of running adjustment inputs.

When the stride length imbalance issue has been added to the runningadjustments inputs or there is not a stride length imbalance issue, themethod continues at step 658 where the processing module determineswhether a ground reaction force (GRF) issue exists. For example, GRF isthe force between the foot and the ground when running. If the GRF istoo low, the person is not driving his or her legs hard enough. If theGRF is too high, then the person may be landing wrong, driving too hard,etc. If the GRF issues exists, the method continues at step 660 wherethe processing module adds the GRF issue to a list of running adjustmentinputs.

When the GRF issue has been added to the running adjustments inputs orthere is not a GRF issue, the method continues at step 662 where theprocessing module determines whether a ground contact issue exists. Forexample, for speed, a runner desired a minimum amount of contact timewith the ground per stride. When the contact time with the ground is toohigh, the runner is losing time. If the ground contact issue exists, themethod continues at step 664 where the processing module adds the groundcontact issue to a list of running adjustment inputs.

When the ground contact issue has been added to the running adjustmentsinputs or there is not a ground contact issue, the method continues atstep 666 where the processing module determines whether a foot positionoffset exists. For example, the processing interprets the correlatedfoot data to determine that foot positioning is offset by at least afoot positioning threshold from an optimal foot positioning. Forexample, the left foot rolls out several inches when striding from theleft foot to left foot contact with the ground. This wastes energy andmay lead to an injury. If there is a foot position offset, the methodcontinues at step 668 where the processing module adds the foot positionoffset to a list of running adjustment inputs.

The method continues at step 670 where the processing module determineswhether any inputs are in the running adjustment inputs. If not, themethod continues at step 674 where no corrective measures are provided.If, however, there is at least one input in the running adjustmentinputs, the method continues at step 672 where the processing modulegenerates one or more corrective measures based on the runningadjustment inputs. The corrective measures include training forimproving stride length, reducing contact time, improving GRF, etc.

FIG. 116 is a logic diagram of another example of a method executed by ashoe sensor system to determine the rotational sport optimization (e.g.,improve weight distribution, improve GRF, improve balance, improvelinear movement, improve rotational movement, improve linear and/orrotation power, etc.). The method begins at step 682 where theprocessing module determines ground reaction force during performance ofan athletic movement of a rotational sport (e.g., baseball, golf,tennis, lacrosse, football, basketball, etc.).

The method continues at step 683 where the processing module determinesweight force vector distribution between medial and lateral side of thefoot and between forefoot and heel based on the ground reaction forces.The method continues at step 684 where the processing module determineswhether the weight force vector distribution is less than optimal. Whenit is not, the method continues at step 688 where no corrective measuresare provided. When the weight force vector distribution is less thanoptimal, the method continues at step 686 where the processing moduledetermines a corrective measure to optimize the weight force vectordistribution during performance of the athletic movement.

In the preceding discussion, various figures were used to illustratevarious aspects of inventive subject matter. If it is determined that aninconsistency existed between two figures, then the inconsistency shallbe resolved in favor of the lower numbered figure.

It is noted that terminologies as may be used herein such as bit stream,stream, signal sequence, etc. (or their equivalents) have been usedinterchangeably to describe digital information whose contentcorresponds to any of a number of desired types (e.g., data, video,speech, text, graphics, audio, etc. any of which may generally bereferred to as ‘data’).

As may be used herein, the terms “substantially” and “approximately”provide an industry-accepted tolerance for its corresponding term and/orrelativity between items. For some industries, an industry-acceptedtolerance is less than one percent and, for other industries, theindustry-accepted tolerance is 10 percent or more. Other examples ofindustry-accepted tolerance range from less than one percent to fiftypercent. Industry-accepted tolerances correspond to, but are not limitedto, component values, integrated circuit process variations, temperaturevariations, rise and fall times, thermal noise, dimensions, signalingerrors, dropped packets, temperatures, pressures, material compositions,and/or performance metrics. Within an industry, tolerance variances ofaccepted tolerances may be more or less than a percentage level (e.g.,dimension tolerance of less than +/−1%). Some relativity between itemsmay range from a difference of less than a percentage level to a fewpercent. Other relativity between items may range from a difference of afew percent to magnitude of differences.

As may also be used herein, the term(s) “configured to”, “operablycoupled to”, “coupled to”, and/or “coupling” includes direct couplingbetween items and/or indirect coupling between items via an interveningitem (e.g., an item includes, but is not limited to, a component, anelement, a circuit, and/or a module) where, for an example of indirectcoupling, the intervening item does not modify the information of asignal but may adjust its current level, voltage level, and/or powerlevel. As may further be used herein, inferred coupling (i.e., where oneelement is coupled to another element by inference) includes direct andindirect coupling between two items in the same manner as “coupled to”.

As may even further be used herein, the term “configured to”, “operableto”, “coupled to”, or “operably coupled to” indicates that an itemincludes one or more of power connections, input(s), output(s), etc., toperform, when activated, one or more its corresponding functions and mayfurther include inferred coupling to one or more other items. As maystill further be used herein, the term “associated with”, includesdirect and/or indirect coupling of separate items and/or one item beingembedded within another item.

As may be used herein, the term “compares favorably”, indicates that acomparison between two or more items, signals, etc., provides a desiredrelationship. For example, when the desired relationship is that signal1 has a greater magnitude than signal 2, a favorable comparison may beachieved when the magnitude of signal 1 is greater than that of signal 2or when the magnitude of signal 2 is less than that of signal 1. As maybe used herein, the term “compares unfavorably”, indicates that acomparison between two or more items, signals, etc., fails to providethe desired relationship.

As may be used herein, one or more claims may include, in a specificform of this generic form, the phrase “at least one of a, b, and c” orof this generic form “at least one of a, b, or c”, with more or lesselements than “a”, “b”, and “c”. In either phrasing, the phrases are tobe interpreted identically. In particular, “at least one of a, b, and c”is equivalent to “at least one of a, b, or c” and shall mean a, b,and/or c. As an example, it means: “a” only, “b” only, “c” only, “a” and“b”, “a” and “c”, “b” and “c”, and/or “a”, “b”, and “c”.

As may also be used herein, the terms “processing module”, “processingcircuit”, “processor”, “processing circuitry”, and/or “processing unit”may be a single processing device or a plurality of processing devices.Such a processing device may be a microprocessor, micro-controller,digital signal processor, microcomputer, central processing unit, fieldprogrammable gate array, programmable logic device, state machine, logiccircuitry, analog circuitry, digital circuitry, and/or any device thatmanipulates signals (analog and/or digital) based on hard coding of thecircuitry and/or operational instructions. The processing module,module, processing circuit, processing circuitry, and/or processing unitmay be, or further include, memory and/or an integrated memory element,which may be a single memory device, a plurality of memory devices,and/or embedded circuitry of another processing module, module,processing circuit, processing circuitry, and/or processing unit. Such amemory device may be a read-only memory, random access memory, volatilememory, non-volatile memory, static memory, dynamic memory, flashmemory, cache memory, and/or any device that stores digital information.Note that if the processing module, module, processing circuit,processing circuitry, and/or processing unit includes more than oneprocessing device, the processing devices may be centrally located(e.g., directly coupled together via a wired and/or wireless busstructure) or may be distributedly located (e.g., cloud computing viaindirect coupling via a local area network and/or a wide area network).Further note that if the processing module, module, processing circuit,processing circuitry and/or processing unit implements one or more ofits functions via a state machine, analog circuitry, digital circuitry,and/or logic circuitry, the memory and/or memory element storing thecorresponding operational instructions may be embedded within, orexternal to, the circuitry comprising the state machine, analogcircuitry, digital circuitry, and/or logic circuitry. Still further notethat, the memory element may store, and the processing module, module,processing circuit, processing circuitry and/or processing unitexecutes, hard coded and/or operational instructions corresponding to atleast some of the steps and/or functions illustrated in one or more ofthe Figures. Such a memory device or memory element can be included inan article of manufacture.

One or more embodiments have been described above with the aid of methodsteps illustrating the performance of specified functions andrelationships thereof. The boundaries and sequence of these functionalbuilding blocks and method steps have been arbitrarily defined hereinfor convenience of description. Alternate boundaries and sequences canbe defined so long as the specified functions and relationships areappropriately performed. Any such alternate boundaries or sequences arethus within the scope and spirit of the claims. Further, the boundariesof these functional building blocks have been arbitrarily defined forconvenience of description. Alternate boundaries could be defined aslong as the certain significant functions are appropriately performed.Similarly, flow diagram blocks may also have been arbitrarily definedherein to illustrate certain significant functionality.

To the extent used, the flow diagram block boundaries and sequence couldhave been defined otherwise and still perform the certain significantfunctionality. Such alternate definitions of both functional buildingblocks and flow diagram blocks and sequences are thus within the scopeand spirit of the claims. One of average skill in the art will alsorecognize that the functional building blocks, and other illustrativeblocks, modules and components herein, can be implemented as illustratedor by discrete components, application specific integrated circuits,processors executing appropriate software and the like or anycombination thereof.

In addition, a flow diagram may include a “start” and/or “continue”indication. The “start” and “continue” indications reflect that thesteps presented can optionally be incorporated in or otherwise used inconjunction with one or more other routines. In addition, a flow diagrammay include an “end” and/or “continue” indication. The “end” and/or“continue” indications reflect that the steps presented can end asdescribed and shown or optionally be incorporated in or otherwise usedin conjunction with one or more other routines. In this context, “start”indicates the beginning of the first step presented and may be precededby other activities not specifically shown. Further, the “continue”indication reflects that the steps presented may be performed multipletimes and/or may be succeeded by other activities not specificallyshown. Further, while a flow diagram indicates a particular ordering ofsteps, other orderings are likewise possible provided that theprinciples of causality are maintained.

The one or more embodiments are used herein to illustrate one or moreaspects, one or more features, one or more concepts, and/or one or moreexamples. A physical embodiment of an apparatus, an article ofmanufacture, a machine, and/or of a process may include one or more ofthe aspects, features, concepts, examples, etc. described with referenceto one or more of the embodiments discussed herein. Further, from figureto figure, the embodiments may incorporate the same or similarly namedfunctions, steps, modules, etc. that may use the same or differentreference numbers and, as such, the functions, steps, modules, etc. maybe the same or similar functions, steps, modules, etc. or differentones.

While transistors may be shown in one or more of the above-describedfigure(s) as field effect transistors (FETs), as one of ordinary skillin the art will appreciate, the transistors may be implemented using anytype of transistor structure including, but not limited to, bipolar,metal oxide semiconductor field effect transistors (MOSFET), N-welltransistors, P-well transistors, enhancement mode, depletion mode, andzero voltage threshold (VT) transistors.

Unless specifically stated to the contra, signals to, from, and/orbetween elements in a figure of any of the figures presented herein maybe analog or digital, continuous time or discrete time, and single-endedor differential. For instance, if a signal path is shown as asingle-ended path, it also represents a differential signal path.Similarly, if a signal path is shown as a differential path, it alsorepresents a single-ended signal path. While one or more particulararchitectures are described herein, other architectures can likewise beimplemented that use one or more data buses not expressly shown, directconnectivity between elements, and/or indirect coupling between otherelements as recognized by one of average skill in the art.

The term “module” is used in the description of one or more of theembodiments. A module implements one or more functions via a device suchas a processor or other processing device or other hardware that mayinclude or operate in association with a memory that stores operationalinstructions. A module may operate independently and/or in conjunctionwith software and/or firmware. As also used herein, a module may containone or more sub-modules, each of which may be one or more modules.

As may further be used herein, a computer readable memory includes oneor more memory elements. A memory element may be a separate memorydevice, multiple memory devices, or a set of memory locations within amemory device. Such a memory device may be a read-only memory, randomaccess memory, volatile memory, non-volatile memory, static memory,dynamic memory, flash memory, cache memory, and/or any device thatstores digital information. The memory device may be in a form asolid-state memory, a hard drive memory, cloud memory, thumb drive,server memory, computing device memory, and/or other physical medium forstoring digital information.

As applicable, one or more functions associated with the methods and/orprocesses described herein can be implemented via a processing modulethat operates via the non-human “artificial” intelligence (AI) of amachine. Examples of such AI include machines that operate via anomalydetection techniques, decision trees, association rules, expert systemsand other knowledge-based systems, computer vision models, artificialneural networks, convolutional neural networks, support vector machines(SVMs), Bayesian networks, genetic algorithms, feature learning, sparsedictionary learning, preference learning, deep learning and othermachine learning techniques that are trained using training data viaunsupervised, semi-supervised, supervised and/or reinforcement learning,and/or other AI. The human mind is not equipped to perform such AItechniques, not only due to the complexity of these techniques, but alsodue to the fact that artificial intelligence, by its verydefinition—requires “artificial” intelligence—i.e., machine/non-humanintelligence.

As applicable, one or more functions associated with the methods and/orprocesses described herein can be implemented as a large-scale systemthat is operable to receive, transmit and/or process data on alarge-scale. As used herein, a large-scale refers to a large number ofdata, such as one or more kilobytes, megabytes, gigabytes, terabytes ormore of data that are received, transmitted and/or processed. Suchreceiving, transmitting and/or processing of data cannot practically beperformed by the human mind on a large-scale within a reasonable periodof time, such as within a second, a millisecond, microsecond, areal-time basis or other high speed required by the machines thatgenerate the data, receive the data, convey the data, store the dataand/or use the data.

As applicable, one or more functions associated with the methods and/orprocesses described herein can require data to be manipulated indifferent ways within overlapping time spans. The human mind is notequipped to perform such different data manipulations independently,contemporaneously, in parallel, and/or on a coordinated basis within areasonable period of time, such as within a second, a millisecond,microsecond, a real-time basis or other high speed required by themachines that generate the data, receive the data, convey the data,store the data and/or use the data.

As applicable, one or more functions associated with the methods and/orprocesses described herein can be implemented in a system that isoperable to electronically receive digital data via a wired or wirelesscommunication network and/or to electronically transmit digital data viaa wired or wireless communication network. Such receiving andtransmitting cannot practically be performed by the human mind becausethe human mind is not equipped to electronically transmit or receivedigital data, let alone to transmit and receive digital data via a wiredor wireless communication network.

As applicable, one or more functions associated with the methods and/orprocesses described herein can be implemented in a system that isoperable to electronically store digital data in a memory device. Suchstorage cannot practically be performed by the human mind because thehuman mind is not equipped to electronically store digital data.

While particular combinations of various functions and features of theone or more embodiments have been expressly described herein, othercombinations of these features and functions are likewise possible. Thepresent disclosure is not limited by the particular examples disclosedherein and expressly incorporates these other combinations.

What is claimed is:
 1. An athlete monitoring system comprises: aplurality of body position beacons, wherein, when an athlete uses theathlete monitoring system, the plurality of body position beacons ispositioned at various locations on the body of the athlete; a localizedradar system operable to: create a localized radar coordinate system inwhich the athlete is positioned; and at a first sampling rate, produce aplurality of frames of body position data based on determining locationof the plurality of body position beacons within the localized radarcoordinate system; and a foot force detection system operable to, at asecond sampling rate: generate a plurality of frames of left foot forcedata; and generate a plurality of frames of right foot force data; and aprocessing module operable to: correlate the plurality of frames of bodyposition data, the plurality of frames of left foot force data, and theplurality of frames of right foot force data to produce integratedground-body interaction data and athletic movement data.
 2. The athletemonitoring system of claim 1 further comprises: the processing modulebeing of the localized radar system and/or of the foot force detectionsystem.
 3. The athlete monitoring system of claim 1 further comprises:the plurality of body position beacons includes a plurality of radiofrequency (RF) devices; the localized radar system is further operableto, during a cycle of the sampling rate: send, by a transmitter of thelocalized radar system, a first beacon signal targeting a first RFdevice of the plurality of RF devices; and receive, by each of at leastthree receivers of the localized radar system, a ring-back signal fromthe first RF device to produce at least three ring-back signals; theprocessing module is further operable to: determine a relative positionof the first RF device with respect to the at least three receivers; andmap the relative position of the of the first RF device to the localizedradar coordinate system.
 4. The athlete monitoring system of claim 3,wherein the determining the relative position of the first RF devicewith respect to the at least three receivers comprises: for a firstreceiver of the at least three receivers determine a first time offsetbetween the first beacon signal and the ring-back signal received by thefirst receiver to produce a first round-trip time; for a second receiverof the at least three receivers determine a second time offset betweenthe first beacon signal and the ring-back signal received by the secondreceiver to produce a second round-trip time; for a third receiver ofthe at least three receivers determine a third time offset between thefirst beacon signal and the ring-back signal received by the thirdreceiver to produce a third round-trip time; calculate a first distancebetween the first RF device and the first receiver based on the firstround-trip time; calculate a second distance between the first RF deviceand the second receiver based on the second round-trip time; calculate athird distance between the first RF device and the third receiver basedon the third round-trip time; and calculate the relative position basedon the first, second, and third distances.
 5. The athlete monitoringsystem of claim 4, wherein the first beacon signal comprises: a patternthat is repeated at a given frequency, wherein ring-back signal includesa delayed representation of the pattern; and the processing module beingfurther operable to: determine a cumulative delay between the firstbeacon signal and the ring-back signal received by the first receiverbased on the delayed representation of the pattern; obtain a processingtime for the RF device to generate the ring-back signal; and determinethe first time offset based on the cumulative delay and the processingtime.
 6. The athlete monitoring system of claim 3, wherein thedetermining the relative position of the first RF device with respect tothe at least three receivers comprises: for a first receiver of the atleast three receivers determine a first power difference between a firstcomponent of the first beacon signal and the ring-back signal receivedby the first receiver; for a second receiver of the at least threereceivers determine a second power difference between a second componentof the first beacon signal and the ring-back signal received by thesecond receiver; for a third receiver of the at least three receiversdetermine a third power difference between a third component of thefirst beacon signal and the ring-back signal received by the thirdreceiver; calculate a first distance between the first RF device and thefirst receiver based on the first power difference and a path lossfunction; calculate a second distance between the first RF device andthe second receiver based on the second power difference and the pathloss function; calculate a third distance between the first RF deviceand the third receiver based on the third power difference and the pathloss function; and calculate the relative position based on the first,second, and third distances.
 7. The athlete monitoring system of claim1, wherein the localized radar system creates the localized radarcoordinate system by: associating an origin of the localized radarcoordinate system with a particular point on the body; establishing az-axis of the localized radar coordinate system to be perpendicular tothe ground, a positive direction away from the ground, and passingthrough the origin; establishing an x-axis of the localized radarcoordinate system to be parallel to the ground, to have a positivedirection to the front of the body, and passing through the origin; andestablishing a y-axis of the localized radar coordinate system to beparallel to the ground, to have a positive direction to the right of thebody, and passing through the origin.
 8. The athlete monitoring systemof claim 1, wherein the processing module correlates the plurality offrames of body position data, the plurality of frames of left foot forcedata, and the plurality of frames of right foot force data by: timealigning a frame of the body position data, a frame of the left footforce data, and a frame of the right foot force data to produce framecorrelated data; determining, based on a plurality of frame correlateddata, force vector motion data from the ground, through the shoes, andinto the body; generating the integrated ground-body interaction dataand athletic movement data based on the force vector motion data.
 9. Theathlete monitoring system of claim 1 further comprises: the localizedradar system and the foot force detection system being contained in apair of shoes.
 10. An athlete monitoring system comprises: a pluralityof body position beacons, wherein, when an athlete uses the athletemonitoring system, the plurality of body position beacons is positionedat various locations on the body of the athlete; a localized radarsystem operable to: create a localized radar coordinate system in whichthe athlete is positioned; and at a sampling rate, produce a pluralityof frames of body position data based on determining location of theplurality of body position beacons within the localized radar coordinatesystem; and a processing module operable to: correlate the plurality offrames of body position data to athletic movement data.
 11. The athletemonitoring system of claim 10 further comprises: the plurality of bodyposition beacons includes a plurality of radio frequency (RF) devices;the localized radar system is further operable to, during a cycle of thesampling rate: send, by a transmitter of the localized radar system, afirst beacon signal targeting a first RF device of the plurality of RFdevices; and receive, by each of at least three receivers of thelocalized radar system, a ring-back signal from the first RF device toproduce at least three ring-back signals; the processing module isfurther operable to: determine a relative position of the first RFdevice with respect to the at least three receivers; and map therelative position of the of the first RF device to the localized radarcoordinate system.
 12. The athlete monitoring system of claim 11,wherein the determining the relative position of the first RF devicewith respect to the at least three receivers comprises: for a firstreceiver of the at least three receivers determine a first time offsetbetween the first beacon signal and the ring-back signal received by thefirst receiver to produce a first round-trip time; for a second receiverof the at least three receivers determine a second time offset betweenthe first beacon signal and the ring-back signal received by the secondreceiver to produce a second round-trip time; for a third receiver ofthe at least three receivers determine a third time offset between thefirst beacon signal and the ring-back signal received by the thirdreceiver to produce a third round-trip time; calculate a first distancebetween the first RF device and the first receiver based on the firstround-trip time; calculate a second distance between the first RF deviceand the second receiver based on the second round-trip time; calculate athird distance between the first RF device and the third receiver basedon the third round-trip time; and calculate the relative position basedon the first, second, and third distances.
 13. The athlete monitoringsystem of claim 12, wherein the first beacon signal comprises: a patternthat is repeated at a given frequency, wherein ring-back signal includesa delayed representation of the pattern; and the processing module beingfurther operable to: determine a cumulative delay between the firstbeacon signal and the ring-back signal received by the first receiverbased on the delayed representation of the pattern; obtain a processingtime for the RF device to generate the ring-back signal; and determinethe first time offset based on the cumulative delay and the processingtime.
 14. The athlete monitoring system of claim 11, wherein thedetermining the relative position of the first RF device with respect tothe at least three receivers comprises: for a first receiver of the atleast three receivers determine a first power difference between a firstcomponent of the first beacon signal and the ring-back signal receivedby the first receiver; for a second receiver of the at least threereceivers determine a second power difference between a second componentof the first beacon signal and the ring-back signal received by thesecond receiver; for a third receiver of the at least three receiversdetermine a third power difference between a third component of thefirst beacon signal and the ring-back signal received by the thirdreceiver; calculate a first distance between the first RF device and thefirst receiver based on the first power difference and a path lossfunction; calculate a second distance between the first RF device andthe second receiver based on the second power difference and the pathloss function; calculate a third distance between the first RF deviceand the third receiver based on the third power difference and the pathloss function; and calculate the relative position based on the first,second, and third distances.
 15. The athlete monitoring system of claim10, wherein the localized radar system creates the localized radarcoordinate system by: associating an origin of the localized radarcoordinate system with a particular point on the body. establishing az-axis of the localized radar coordinate system to be perpendicular tothe ground, a positive direction away from the ground, and passingthrough the origin; establishing an x-axis of the localized radarcoordinate system to be parallel to the ground, to have a positivedirection to the front of the body, and passing through the origin; andestablishing a y-axis of the localized radar coordinate system to beparallel to the ground, to have a positive direction to the right of thebody, and passing through the origin.